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Seven Good Reasons for Mobile Agents
... There has also been a keen interest in the use of mobile intelligent agents in many areas including health (Miller and Sankaranarayanan 2010;Kirn 2002;Mateo et al. 2007;Varshney 2014a;b) due to the number of proposed benefits and the inherent features of mobile agents (Lange and Oshima 1999). These features include: autonomy, mobility, proactive, collaborative and goal oriented (Lange and Oshima 1999). ...
... There has also been a keen interest in the use of mobile intelligent agents in many areas including health (Miller and Sankaranarayanan 2010;Kirn 2002;Mateo et al. 2007;Varshney 2014a;b) due to the number of proposed benefits and the inherent features of mobile agents (Lange and Oshima 1999). These features include: autonomy, mobility, proactive, collaborative and goal oriented (Lange and Oshima 1999). These features can provide many benefits to medical systems. ...
... Mobile intelligent agents are autonomous movable code that are capable of migrating from one host to another carrying data and also its state to continue its execution (Lange and Oshima 1999). Mobile agents usually have all or most of these properties: autonomy, mobility, adaptive/learning, goal oriented, active/proactive, collaborative/communicative (Franklin and Graesser 1996). ...
Prescribing the right drugs for a patient is a difficult task that takes into consideration several factors. The Institute of Medicine (IOM), U.S.A., has reported based on two major studies (1999–2001 & 2006) that prescribing the wrong medication is a big problem, and the effects can sometimes be fatal. To address this problem, we designed and implemented, a distributed intelligent mobile agent-based system by the name, OptiPres. This system will be used by doctors on their smart phones while prescribing medicines. It will assist them in making more informed decisions by either choosing the optimal solution from processing a repository of past decisions or by presenting a set of possible drugs and using criteria specified by them to identify the optimal drug. The evaluation of OptiPres was done by comparing its recommended outcome of three predefined medical scenarios against the recommendations from a group of doctors and the World Health Organization (WHO) manual entitled:‘Guide to Good Prescribing’. The results indicate that OptiPres is effective in prescribing optimal drugs and in reducing the cognitive burden on doctors, especially in subjective decision making contexts where they have to consider multiple parameters.
... Mobility is an orthogonal property of agents, independent of other properties. While any distributed application can be implemented by only using static agents, development and deployment can be improved by using agents that are mobile, with the effect of transferring not only data, but also behaviors, through the network, while keeping both the behavior and the data encapsulated in an autonomous entity [1]. ...
Current multi-agent frameworks usually use centralized, fixed communication infrastructures for the entities that are deployed using them. This decreases the robustness of the system but is less challenging when having to deal with mobile agents that can migrate between nodes. We introduce, in the context of the FLASH-MAS (Fast and Lightweight Agent Shell) multi-entity deployment framework, methods to build decentralized interaction infrastructures which support migrating entities. We discuss the WS-Regions (WebSocket Regions) communication protocol, a proposal for interaction in deployments using multiple communication methods, and a mechanism to facilitate using arbitrary names for entities. The WS-Regions Protocol is compared against Jade (the Java Agent Development Framework), the most popular agent deployment framework, with a favorable trade-off between decentralization and performance.
... This means that the orchestration should be able to cope with dynamically available and mobile resources, such as UAVs, and may request deployment of needed nodes in certain locations in order to achieve the requested MCS functionality (coverage, service supporting nodes, etc.). For Edge (and Fog) a lightweight and relatively simple virtualization technology should be used (for example containers, ClickOs [53], OSGi/JADE [54] or mobile agents' [55]). VMCS has some specific requirements concerning Edge orchestration, which have to be considered: ...
Mission critical solutions are essential for providing communications and services in the case of the troubles with connectivity that are often found in infrastructure-based solutions. Such solutions are typically used in the case of disasters, lack of energy, etc. There exist several narrowband solutions that provide countrywide coverage in certain countries. In recent years, the activities related to creating mission-critical broadband solutions based on Long Term Evolution (LTE) have led to the definition of LTE Mission Critical (LTE-MC). Both solutions ignore virtualization and require dedicated mobile terminals as a part of the mission-critical communication solution. This paper describes the opportunities, open issues and a proposal of a solution that exploits Unmanned Aerial Vehicles (UAVs) and network virtualization for mission-critical services. The presented approach combines Cloud/Edge and Fog orchestration to efficiently use all the available resources, including virtualized resources of the end-user devices
This paper was part of a Special Issue of MDPI - Energies on Carrier-Grade Solution for Unmanned Aerial Vehicles.
... Agents can traverse the system carrying information collected at nodes that they are visiting, and process tasks on each node using the information. In other words, agents can encapsulate the process code and data, which simplifies design of distributed systems [3], [4]. ...
In this paper, we consider the partial gathering problem of mobile agents in arbitrary networks. The partial gathering problem is a generalization of the (well-investigated) total gathering problem, which requires that all the agents meet at the same node. The partial gathering problem requires, for a given positive integer g, that each agent should move to a node and terminate so that at least g agents should meet at each of the nodes they terminate at. The requirement for the partial gathering problem is no stronger than that for the total gathering problem, and thus, we clarify the difference on the move complexity between them. First, we show that agents require Ω(gn+m) total moves to solve the partial gathering problem, where n is the number of nodes and m is the number of communication links. Next, we propose a deterministic algorithm to solve the partial gathering problem in O(gn+m) total moves, which is asymptotically optimal in terms of total moves. Note that, it is known that agents require Ω(kn+m) total moves to solve the total gathering problem in arbitrary networks, where k is the number of agents. Thus, our result shows that the partial gathering problem is solvable with strictly fewer total moves compared to the total gathering problem in arbitrary networks.
... Mobile agents have received much attention in the last decade because of their advantages in accessing distributed recourses in a low-bandwidth network. By migrating to information recourse, an agent can invoke resource operations locally, eliminating the network transfer of intermediate data and also the agent technology provide multiple advantages [1] to a distributed system like electronic business. In spite of the inherent advantages, the reliability of the agent platform and computer communication network is a factor that may affect the performance, availability, and strategy of mobile agent systems [2] and hence the deployment of such systems. ...
Mobile agent technology has become a new paradigm for distributed real-time systems
because of their inherent advantages. In any distributed system, along with other issues,
survivability and fault tolerance are vital issues for deploying mobile-agent systems. E-business
becoming a prominent domain for deploying agent technology, it also faces reliability
problems due to the failure of agent platform and communication link etc. The reliability is a
factor that may affect the performance, availability, and strategy of mobile agent systems. In
this paper, reliability issues of mobile agents, particularly in an e-business environment, are
discussed. Models for mobile agent reliability have been developed, and a Shopping Consultant
Agent System (SCAS) is built as an experimental mobile agent based e-business application.
Reliability problems of the system have been identified, and two simple solutions namely
periodic scan and forward echo are implemented. The reliability improvement gained by the
solutions is evaluated according to the reliability model developed in this paper.
Keywords: E-Business, Reliability, Multi-Agent System
... MA is a special type of software entity that migrates among SNs to gather data [8,13] . In comparison with CS paradigm, MA paradigm has many features [4,[14][15][16] that makes it more suitable for WSNs. It is important to note that the itinerary planning for MA is the most challenging issue with this paradigm. ...
Mobile agent (MA)-based wireless sensor networks present a good alternative to the traditional client/server paradigm. Instead of sending the data gathered by each node to the sink as in client/server, MAs migrate to the sensor nodes (SNs) to collect data, thus reducing energy consumption and bandwidth usage. For MAs, to migrate among SNs, an itinerary should be planned before the migration. Many approaches have been proposed to solve the problem of itinerary planning for MAs, but all of these approaches are based on the assumption that MAs visit all SNs. This assumption, however, is inefficient because of the increasing size of the MAs after visiting each node. Also, in case of node(s) failure, as it is often the case in WSNs, the MAs may not be able to migrate among SNs. None of the proposed approaches takes into consideration the problem of fault tolerance. In this paper, we propose multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks (MAEF) to plan itineraries for MAs. This can be achieved by grouping nodes in clusters and planning itineraries efficiently among cluster heads (CHs) only. What is more, an alternative itinerary is planned in case of node(s) failure. The simulation result clearly shows that our novel approach performs better than the existing ones.
... MA is a special kind of software entity that moves among SNs to collect data (Khaleghi et al. 2013). MA paradigm has many features (Franklin and Graesser 1997;Chess et al. 1997;Fuggetta et al. 1998;Lange and Oshima 1999) that make it more suitable for WSNs. ...
Mobile Agent (MA) paradigm for data aggregation in wireless sensor networks (WSNs) presents a distributed computing paradigm which has proved its efficiency in comparison to the traditional client–server computing paradigm. In terms of energy consumption and overall time response, MA computing paradigm presents a better alternative. Instead of sending the collected data to the sink as in client/server, MA moves to sensor nodes (SNs) for data collection. For MA, to move among SNs, an itinerary should be planned before the migration. Many approaches have been proposed to solve the problem, but all approaches did not take into consideration the fault tolerance problem, even though WSNs are prone to failure. In this respect, we propose Energy efficient and fault tolerant distributed algorithm for data aggregation in wireless sensor networks (EFTA) to plan the itinerary for MA and another alternative itinerary in case of node(s) failure. Our algorithm adopts a clustering method to group SNs in clusters then plans the itinerary among those clusters efficiently. Also an alternative itinerary based fault tolerance is proposed. Simulation results show that our algorithm performs better than other existing ones.
Malware used in advanced persistent threats often establish a covert channel. By means of such a channel, the malware can communicate with external Command & Control servers or send classified data to a server controlled by the attacker. In military networks, these covert transmissions are a security problem with significant impact on the success of a military operation. Mobile agents in combination with machine learning are particularly suitable to detect and mitigate these type of attacks. However, a mobile agent needs to be trained before its deployment. In this paper, a concept is defined how federated learning can be used to train the mobile agents in tactical networks if the training data is distributed on the nodes of a tactical network. Furthermore, we propose an algorithm to select the nodes that are involved in the training. The proposed concepts and methods are evaluated regarding their efficiency. The evaluation considers in particular federated learning in the inter-organizational tactical networks because multinational armed forces are often involved in modern military operations.
Named data networking (NDN) presents a huge opportunity to tackle some of the unsolved issues of IP‐based vehicular ad hoc networks (VANET). The core characteristics of NDN such as the name‐based routing, in‐network caching, and built‐in data security provide better management of VANET proprieties (e.g., the high mobility, link intermittency, and dynamic topology). This study aims at providing a clear view of the state‐of‐the‐art on the developments in place, in order to leverage the characteristics of NDN in VANET. We resort to a systematic literature review (SLR) to perform a reproducible study, gathering the proposed solutions and summarizing the main open challenges on implementing NDN‐based VANET. There exist several related studies, but they are more focused on other topics such as forwarding. This work specifically restricts the focus on VANET improvements by NDN‐based routing (not forwarding), caching, and security. The surveyed solution herein presented is performed between 2010 and 2021. The results show that proposals on the selected topics for NDN‐based VANET are recent (mainly from 2016 to 2021). Among them, caching is the most investigated topic. Finally, the main findings and the possible roadmaps for further development are highlighted. A systematic review on the realization of NDN‐based VANET, specifically for NDN‐based routing (not forwarding), caching and security issues, was performed for the period of 2010‐2021. The study concluded that caching has been the more investigated topic. There are, however, some gaps still to be tackled. For instance, a means to further reduce the broadcast storm problem in routing may include leveraging all overhead packets for location‐aware, and leverage caching for better routing decision.
In this paper, we consider the relaxed version of the uniform deployment problem, called the almost uniform deployment problem, of mobile agents in synchronous dynamic bidirectional ring networks. The uniform deployment problem requires agents to spread uniformly in the ring. So far, uniform deployment has been considered in static graphs. In this paper, we extend the target topology to a dynamic one. Concretely, in this paper we consider 1-interval connected rings, that is, one of the links in the ring may be missing at each time step. However, we show that the uniform deployment problem cannot be solved in 1-interval connected rings. Hence, we consider the relaxed version of the uniform deployment problem, called the almost uniform deployment problem, which requires that all agents other than one agent spread uniformly in the ring. We call such a problem the almost uniform deployment problem. In this paper, we aim to clarify the solvability of the almost uniform deployment problem and the algorithm performance, focusing on global knowledge given to the agents. To the best of our knowledge, this is the first research considering (a variant of) uniform deployment in dynamic networks. First, we consider agents with knowledge of the number n of nodes. In this case, we show that our algorithm can solve the problem with O(klogn) memory space per agent, O(nlogk) rounds, and a total number of O(kn) moves, where k is the number of agents. Next, we consider agents without knowledge of n but with knowledge of k. In this case, when k≥4, we show that our algorithm can also solve the problem but requires O(klogn) memory space per agent, O(n2) rounds, and a total number of O(n2) moves. These results mean that the almost uniform deployment problem can be solved in dynamic rings, and agents with knowledge of n can solve the problem more efficiently than agents with knowledge of k.
Computing has emerged from traditional computers to pervasive scenarios where smart wearable and mobile devices are essential to provide human-centric uninterrupted services anywhere and at any time. Wearable computing systems, along with their enabling technology known as Body Sensor Network, represent a ground-breaking innovation with extremely diversified applications spanning from mobile health, wellness, virtual and augmented reality, security, to affective human-machine interaction, to name a few. This article focuses on the several computational aspects coming into play at design, implementation, information processing, and deployment levels, which are required to effectively support this growing technology. The article also discusses development methods, software middleware, and programming frameworks appeared to cope with the several related challenges that arise from data collection to knowledge extraction.
Current IaaS (infrastructure as a service) cloud service may not satisfy communication QoS (quality of service) requirements of delay‐sensitive network applications, if there is a significant physical distance between a server of the network application (NetApp server) at a data center and its network application clients (NetApp clients). In order to improve communication QoS of NetApp clients, we propose server migration service (SMS) in this article. SMS allows NetApp servers to migrate among different locations in the network (1) to optimally locate themselves in relation to NetApp clients and mitigate the QoS degradation caused by location‐related factors (ie, propagation delays on network links) and (2) to optimally distribute traffic load over routers and processing load over (physical) computers and decrease the energy consumption. We develop a mixed‐integer programming model that determines when and to which locations NetApp servers migrate to minimize the total operating cost of SMS, that is, the sum of the monetary penalty incurred due to QoS violation and energy cost incurred due to energy consumption, while preventing NetApp servers from excessively migrating and adversely impacting QoS of the non‐SMS service that share the resource of the substrate network with SMS. Simulation results show that the model developed in this article achieves up to 42% lower total operating cost of SMS compared to the model that only minimizes the monetary penalty of SMS without considering the energy cost of SMS.
The unified modeling language (UML) is used for the specification, visualization, and documentation of object-oriented software systems. Mobile UML (M-UML) is an extension of UML that considers mobility aspects, and a mobile statechart is an extension of the standard UML diagram that deals with the requirements for modeling, specifying, and visualizing mobile agent-based systems. However, mobile statecharts inherit UML’s lack of formal notation for analysis and verification purposes. The rewriting logic language Maude is a formal method that deals with mobile computations. In this paper, we propose a formalization of M-UML statechart diagrams using Maude to provide formal semantics for such diagrams. The generated Maude specifications are then used to analyze and check the systems using Maude analytical tools. This approach is illustrated through an example.
Digital Twin (DT) bridges the physical and virtual worlds and provides technical support to the virtualization of the real production scene. However, with the ubiquitous upgrading of the industrial infrastructure, DT systems present an independent and self-contained pattern that causes repeated constructions, stove-piped projects, and cumbersome communication. Based on the Quality of Service (QoS) considerations, this paper proposes an enabling technology framework combining semantic resource modeling with real-time industrial object transmission to improve the performance of DT and overcome these challenges. Firstly, an enhanced modeling methodology including the industrial object meta-model and the industrial object model is designed. Heterogeneous devices are modeled comprehensively, ranging from states, functions, events, interoperability, and flexibility. By formulating the unified specification to achieve standardization and generalization, workers can customize and reuse the models flexibly according to the volatile working environment. Secondly, a real-time industrial object transmission mechanism ensures high fidelity to the physical world and provides unified interfaces for value-added services. While realizing these primary communication functions in real-time, QoS factors and other advanced performances (i.e., reliability, adaptability, robustness) are fulfilled by introducing a decoupling model, a dual-channel network, and a backup strategy. Under the orchestration of all these works, a robust DT system could be developed readily. Finally, a case study is presented to verify the effectiveness of the proposed framework. The results show that interoperability, scalability, microsecond latency, and other strict requirements are realized.
In this paper, we consider the partial gathering problem of mobile agents in synchronous dynamic bidirectional rings. The partial gathering problem is a generalization of the (well-investigated) total gathering problem, which requires that all k agents distributed in the network terminate at a non-predetermined single node. The partial gathering problem requires, for a given positive integer \(g\,(< k)\), that agents terminate in a configuration such that either at least g agents or no agent exists at each node. The requirement for the partial gathering problem is strictly weaker than that for the total gathering problem, and thus it is interesting to clarify the difference in the move complexity between them. So far, partial gathering has been considered in static graphs. In this paper, we consider this problem in 1-interval connected rings, that is, one of the links in the ring may be missing at each time step. In such networks, we aim to clarify the solvability of the partial gathering problem and the move complexity, focusing on the relationship between values of k and g. First, we consider the case of \( 3g\le k\le 8g-2\). In this case, we show that our algorithm can solve the problem with the total number of O(kn) moves, where n is the number of nodes. Since \(k = O(g)\) holds when \(3g \le k \le 8g-2\), the move complexity O(kn) in this case can be represented also as O(gn). Next, we consider the case of \(k\ge 8g - 3\). In this case, we show that our algorithm can also solve the problem and its move complexity is O(gn). These results mean that, when \(k\ge 3g\), the partial gathering problem can be solved also in dynamic rings. In addition, agents require a total number of \(\varOmega (gn)\) (resp., \(\varOmega (kn)\)) moves to solve the partial (resp., total) gathering problem. Thus, the both proposed algorithms can solve the partial gathering problem with the asymptotically optimal total number of O(gn) moves, which is strictly smaller than that for the total gathering problem.
This paper analyzes the reasons for the formation of security problems in mobile agent systems, and analyzes and compares the security mechanisms and security technologies of existing mobile agent systems from the perspective of blocking attacks. The host guiding mobile agent shielding technology is sorted out, a technique to intensify the reliability shield of mobile representative (named as IEOP procedure) is proposed. The method first encrypts the mobile agent code using the encryption function, and then encapsulates the encrypted mobile agent with the improved EOP protocol IEOP, and then traces the suspicious execution result. Experiments show that using this method can block most malicious attacks on mobile agents, and can protect the integrity and confidentiality of mobile agents, but the increment of mobile agent tour time is not large.
Mobile agents (agents) are objects which can migrate autonomously in a distributed system and execute actions at visited nodes. One of the most fundamental problems of agents is exploration, which requires that each node should be visited by at least one agent. For a long time, researchers focus on exploration of static networks while exploration of dynamic networks has been studied recently. In this paper, we consider exploration of a dynamic torus under some constraints on the dynamics (or topology changes). An n×m torus (3≤n≤m) is considered as a collection of n row rings and m column rings. The constraint on the dynamics is that each ring should be 1-interval connected, which allows at most one link to be missing at any time in each ring. For the n×m dynamic torus, we propose exploration algorithms with and without the link presence detection. With the link presence detection, an agent can detect which incident links are missing (if some link is missing) before determining its next move. On the other hand, without the link presence detection, an agent has to determine its next move without knowing which incident links are missing, which makes the agent stay on the same node when it tries to move through a missing link. The main contribution of this paper is to clarify the necessary and sufficient number of agents to explore an n×m dynamic torus with and without the link presence detection. Specifically, it is proven that, without the link presence detection, n+1 agents are necessary and sufficient to explore the n×m dynamic torus. It also proven that, with the link presence detection, ⌈n/2⌉+1 agents are necessary and sufficient when n≠4 and, ⌈n/2⌉+2 (i.e., four) agents are necessary and sufficient when n=4 to explore the n×m dynamic torus. With respect to the time complexity, we propose asymptotically time-optimal algorithms with and without the link presence detection.
In this paper, we consider the uniform deployment problem of mobile agents in synchronous dynamic bidirectional rings, which requires agents to spread uniformly in the ring. So far, uniform deployment has been considered in static graphs. In this paper, we consider this problem in 1-interval connected rings, that is, one of the links may be missing at each time step. In such networks, we aim to clarify the solvability of the uniform deployment problem, focusing on global knowledge given to the agents. To the best of our knowledge, this is the first research considering uniform deployment in dynamic networks. First, we consider agents with knowledge of the number n of nodes. In this case, we show that our algorithm can solve the problem with O(klogn) memory space per agent, O(nlogk) rounds, and a total number of O(kn) moves, where k is the number of agents. Next, we consider agents without knowledge of n but with knowledge of k. In this case, when k≥4, we show that our algorithm can also solve the problem but requires O(klogn) memory space per agent, O(n2) rounds, and a total number of O(n2) moves. These results mean that the uniform deployment problem can be solved also in dynamic rings.
This paper proposes an architecture that can support autonomous mobile agents performing intrusion prevention activities on a heterogeneous network. The division of duties performed by the agents in the system ensures the agents are able to remain distributed throughout the network architecture to eliminate single points of failure. The distributed nature of the architecture reduces the workload on network clients and eliminates duplication of effort wherever possible. The use of virtual machine interfaces between the hardware and the network connection isolates the hardware interface in order to maintain trust and integrity of the connection and reduce the potential for an attacker using a trusted resource to damage network assets. Virtual machine connections allow a potential malware infection that invades the network environment to be safely observed for unusual behavior patterns using heuristic analysis to provide new evidentiary indicators that can be used to identify the malware during future outbreaks.
Mobile agent planning (MAP) is one of the most important techniques in the mobile computing paradigm to complete a given task in the most efficient manner. To tackle this challenging NP-hard problem, Hopfield-Tank neural network is modified to provide a dynamic approach which not only optimizes the cost of mobile agents in a spatio-temporal computing environment, but also satisfies the location-based constraints such as the starting and ending nodes of the routing sequence which must be the home site of the traveling mobile agent. Meanwhile, the energy function is reformulated into a Lyapunov function to guarantee the convergence to a stable state and the existence of valid solutions. Moreover, the objective function is designed to estimate the completion time of a valid solution and to predict the optimal routing path. This method can produce solutions rapidly that are very close to the minimum cost of the location-based and time-constrained distributed MAP problem.
Mobile agents have been proposed for key applications such as forensics analysis, intrusion detection, e-commerce, and resource management. Yet, they are vulnerable to various security threats by malicious hosts or intruders. Conversely, genuine platforms may run malicious agents. It is essential to establish a truly secure framework for mobile agents to gain trust of clients in the system. Failure to accomplish a trustworthy secured framework for Mobile Agent System (MAS) will limit their deployment into the key applications. This chapter presents a comprehensive taxonomy of various security threats to Mobile Agent System and the existing implemented security mechanisms. Different mechanisms are discussed, and the related security deficiencies are highlighted. The various security properties of the agent and the agent platform are described. The chapter also introduces the properties, advantages, and roles of agents in various applications. It describes the infrastructure of the system and discusses several mobile agent frameworks and the accomplished security level.
Recently, agent-based software technology (ABST) has received widespread attention from the research community and users. However, security issues facing ABST are critical. When a mobile agent migrates from their home machine to perform tasks, the agent becomes vulnerable to attacks by the destination machine, which has full control over the visiting mobile agent. To address this security issue, we propose a dummy task selection (DTS) approach to protect the mobile agent by confusing the attacker (destination machine) with regard to distinguishing the real task among dummy attacks. Considering that side information may be employed by the attacker to perform advanced attacks, we introduce improved DTS as an enhancement of the DTS approach. The improved DTS approach generates strong dummy tasks based on execution probabilities that lead to the highest entropy. Unlike previous approaches, the improved-DTS approach performs the full protection mechanism at the home machine, which in turn limits the ability of the attacker to control the visiting mobile agent. Compared to previous approaches, both the DTS and improved-DTS methods achieved better performance and higher resistance to advanced active attacks such as alternation, collusion, and DoS attacks.
In this paper, we consider the partial gathering problem of mobile agents in asynchronous unidirectional ring networks. The partial gathering problem is a generalization of the (well-investigated) total gathering problem, which requires that all the k agents distributed in the network terminate at a single node. The partial gathering problem requires, for a given positive integer g(<k), that all the agents terminate in a configuration such that either at least g agents or no agent exists at each node. The requirement for the partial gathering problem is strictly weaker than that for the total gathering problem, and thus it is interesting to clarify the difference on the move complexity between them. In this paper, we aim to solve the partial gathering problem for agents without identifiers or any global knowledge such as the number k of agents or the number n of nodes. We consider deterministic and randomized cases. First, in the deterministic case, we show that the set of unsolvable initial configurations is the same as that for the case of agents with knowledge of k. In addition, we propose an algorithm that solves the problem from any solvable initial configuration in a total number of O(gn) moves. Next, in the randomized case, we propose an algorithm that solves the problem in a total number of O(gn) moves in expectation from any initial configuration. Note that g<k holds and agents require a total number of Ω(gn) (resp., Ω(kn)) moves to solve the partial (resp., total) gathering problem. Thus, our algorithms can solve the partial gathering problem in asymptotically optimal total number of moves without identifiers or global knowledge, and the total number of O(gn) moves is strictly smaller than that for the total gathering problem.
In wireless sensor networks (WSNs), mobile agent (MA) is a new paradigm that has gained more attention lately. In this paradigm, MA migrates among sensor nodes (SNs) for data fusion. However, in comparison to traditional client/server paradigm; where each SN in the network sends its collected data to the sink, MA presents a good alternative in terms of energy consumption, response time and network lifetime. In this paradigm, the most critical properties of MA is the itinerary planning, it has always been an issue and a NP-hard problem. In this paper, we present a survey of the proposed itinerary planning approaches for MAs in WSNs. MA itinerary planning techniques can be classified into three categories: static itinerary planning, dynamic itinerary planning and hybrid itinerary planing. The benefits and shortcomings of different MA itinerary planning approaches are presented. Furthermore, we implement, simulate and compare the most prominent itinerary planning algorithms upon a common parameter space, making realistic network-level assumptions.
It is estimated that there will be approximately 125 billion Internet of Things (IoT) devices connected to the Internet by 2030, which are expected to generate large amounts of data. This will challenge data processing capability, infrastructure scalability, and privacy. Several studies have demonstrated the benefits of using distributed intelligence (DI) to overcome these challenges. We propose a Mobile-Agent Distributed Intelligence Tangle-Based approach (MADIT) as a potential solution based on IOTA (Tangle), where Tangle is a distributed ledger platform that enables scalable, transaction-based data exchange in large P2P networks. MADIT enables distributed intelligence at two levels. First, multiple mobile agents are employed to cater for node level communications and collect transactions data at a low level. Second, high level intelligence uses a Tangle based architecture to handle transactions. The Proof-of-Work offloading computation mechanism improves efficiency and speed of processing, while reducing energy consumption. Extensive experiments show that transaction processing speed is improved by using mobile agents, thereby providing better scalability.
In this paper, we consider the uniform deployment problem of mobile agents in asynchronous unidirectional ring networks. This problem requires agents to spread uniformly in the network. In this paper, we focus on the memory space per agent required to solve the problem. We consider two problem settings. The first setting assumes that agents have no multiplicity detection, that is, agents cannot detect whether another agent is staying at the same node or not. In this case, we show that each agent requires Ω(logn) memory space to solve the problem, where n is the number of nodes. In addition, we propose an algorithm to solve the problem with O(k+logn) memory space per agent, where k is the number of agents. The second setting assumes that each agent is equipped with the weak multiplicity detection, that is, agents can detect whether another agent is staying at the same node or not, but cannot get any other information about the number of the agents. Then, we show that the memory space per agent can be reduced to O(logk+loglogn). To the best of our knowledge, this is the first research considering the effect of the multiplicity detection on memory space required to solve problems.
The organizational aspects are currently getting a great attention within the multi-agent systems (MAS) community. The motivation towards this trend is finding a way to handle the increasing complexity and distribution of modern agent-based applications using higher order abstractions such as agent organizations. It is a transition from concerning the micro level (individual agents) to concerning the macro level (the whole system) to handle complexity. A large number of MAS organizational models can be found in MAS literature. Some of them adopt the ACMAS (Agent-Centered MAS) viewpoint and others adopt the OCMAS (Organizational-Centered MAS) viewpoint. Each of the ACMAS and OCMAS viewpoints has its advantages and disadvantages; therefore, combining them into a hybrid model is expected to give us the chance to take benefit of their advantages and avoid their disadvantages. This chapter presents our recent work towards the conceptual design of a hybrid MAS organizational model that combines both of the ACMAS and OCMAS viewpoints.
Multiagent systems have been a fascination for research community and are often seen as an intelligent solution to many complex real world problems. Researchers have been active in the domain since last three decades and many developments pertaining to theoretical design and practical developments of multiagent systems are worth appreciating. The growth in MAS is multidirectional ranging from conceptual ideas to practical implementations and from the wide range of applications; it appears that multiagent systems are proving to be universal. The paper presents a concise survey of developments in MAS highlighting the important contributions in the field and also questions the universal applicability of agents.
Centralization has become a de facto standard for implementing networked environments such as the Cyber–Physical Systems (CPS). Though easy to implement and control, centralized systems are difficult and expensive to scale in terms of the number of devices and the flow of information. This set of circumstances calls for a decentralized and distributed architecture for realizing such networked systems. However, due to the absence of global information in decentralized systems, one of the primary challenges is to find the best solution for problems distributed across the devices which are part of the CPS. Since the problems are distributed and no participating device has access to the full information, the devices may need to interact and share the information to select the best solution for a problem occurred. In this paper, we present a decentralized and distributed mechanism, which adapts to a stream of varying problems and continuously evolves and learns the best mappings between the problems and their associated solutions. The proposed approach integrates the concepts propounded in the three major Immune theories and can cater to real-world situations. The evolved mappings are shared across the physical network, thereby accelerating the search for the best set of solutions. In order to validate the performance of the proposed mechanism, we present the results obtained from solving a problem of sorting a stream of varying data in an emulated decentralized and distributed manner. To substantiate its working in real-world scenarios, we also describe the results obtained by embodying the system in real robots that discover the best path-following algorithms.
In this paper, we consider the partial gathering problem of mobile agents in asynchronous unidirectional rings. This problem requires that, for a given positive integer g, all the agents terminate in a configuration such that at least g agents or no agent exist at each node. While the previous work achieves move-optimal partial gathering using distinct IDs or knowledge of the number of agents, in this paper we aim to achieve this without such information. We consider deterministic and randomized cases. First, in the deterministic case, we show that unsolvable initial configurations exist. In addition, we propose an algorithm to solve the problem from any solvable initial configuration in O(gn) total number of moves, where n is the number of nodes. Next, in the randomized case, we propose an algorithm to solve the problem in O(gn) expected total number of moves from any initial configuration. Since agents require \(\varOmega (gn)\) total number of moves to solve the partial gathering problem, our algorithms can solve the problem in asymptotically optimal total number of moves without global knowledge.
Aiming at the security and trust management of mobile agent system in cloud computing environment, based on the simple public key infrastructure (SPKI) trust mechanism, a mobile agent system objective trust peer management model (MAOTM) is proposed to solve the problem of identity authentication, operation authorization and access control in the mobile agent system; On this basis, the Human Trust Mechanism (HTM) is used to study the subjective trust formation, trust propagation and trust evolution law, and the subjective trust dynamic management algorithm (MASTM) is proposed. Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data, the public trust host selection algorithm is given. The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host, so as to enhance the security interaction between the mobile agent and the host. The simulations of the proposed algorithms are verified and proved to be feasible and effective.
Anomalies and faults are inevitable in computer networks, today more than ever before. This is due to the large scale and dynamic nature of the networks used to process big data and to the ever-increasing number of ad-hoc devices. Beyond natural faults and anomalies occurring in a network, threats proceeding from attacks conducted by malicious intruders must be considered. Consequently, there is often a need to quickly isolate and even repair a fault in a network when it appears. Furthermore, despite the presence in a network of faults stemming from malicious entities, we need to identify the latter and their behaviours, and develop protocols resilient to their attacks. Thus, defining models to capture the dangers inherent to various faults, anomalies and threats in a network and studying such threats, has become increasingly important and popular.
This chapter reviews current technologies used to build secure agents. A wide spectrum of mechanisms to provide security to agent-based systems is provided, giving an overview with the main agent-based systems and agent-oriented tools. An evaluation of security mechanisms is done that identifies security weaknesses. This review covers from the initial approaches to the more recent mechanisms. This analysis draws attention to the fact that these systems have traditionally neglected the need of a secure underlying infrastructure.
In this paper, we consider the uniform deployment problem of mobile agents in asynchronous unidirectional ring networks. This problem requires agents to spread uniformly in the network. In this paper, we focus on the memory space per agent required to solve the problem. We consider two problem settings. The first setting assumes that agents have no multiplicity detection, that is, agents cannot detect whether another agent is staying at the same node or not. In this case, we show that each agent requires \(\varOmega (\log n)\) memory space to solve the problem, where n is the number of nodes. In addition, we propose an algorithm to solve the problem with \(O(k + \log n)\) memory space per agent, where k is the number of agents. The second setting assumes that each agent is equipped with the weak multiplicity detection, that is, agents can detect another agent staying at the same node, but cannot learn the exact number. Then, we show that the memory space per agent can be reduced to \(O(\log k + \log \log n)\). To the best of our knowledge, this is the first research considering the effect of the multiplicity detection on memory space required to solve problems.
Mobile agents are examples of distributed systems which may dispute for the same resources on their hosts. Treating such concurrency adequately is essential, particularly in real-time applications. Due to intrinsic time restrictions, mobile agents in real-time environments are only considered successful if they fulfill their mission by respecting their deadlines. Scheduling algorithms with different policies can be applied in these scenarios. However, the efficiency of these algorithms may deviate according to the missions and deadlines of the mobile agents. Also, these algorithms can be preemptive, or calculate the order of executions without interrupting an ongoing task. In this paper, we propose a middleware extension to the JADE platform that brings real-time scheduling support with preemption to mobile agents. The proposed solution uses best effort scheduling policy in the context of soft real-time applications. We evaluate the performance of the scheduling algorithms, with and without preemption, and the impact of the selected algorithms on mission fulfillment. The results of the proposed middleware showed a great improvement on mission accomplishment when compared to the FIFO algorithm provided by the JADE platform.
Background
The scaling up of the MANETs is an important criterion to consider since the nodes have to maintain the updated routing information. Generally, agents are deployed to balance the load. However, a single agent performance may not be satisfactory, if the network has a large set of nodes. Hence, the agents are necessary once the network size increases, but the launching of Agents in the network involves computational complexity, power consumption and in turn, increase network traffic. This paper addresses the impact of multiple agent deployments in MANETs to quantify the favourable number of Agents in MANETs that can balance the computational overhead as well as the performance gain by involving multiple agents in MANETs.
Methods
The behavior of a varying number of agents in a dynamic network environment launched by a node is analysed across different network metrics. After that, considering all the constraints affecting the network performance, the optimal number of agents is determined using F-Min- Constrained optimization technique.
Result
The Perito-optimal points are generated that shows the approximately near most optimal points to the exact solution.
Conclusion
The paper tries to strike a balance between the constraints like power consumption involved in the launch of Multiple Agents in the network.
Mobile Agent systems are prevalent in Distributed Environment due to the autonomy and adaptability in diversified situations. Mobile Agents are capable of movement from one platform to another and hence it is a need to ensure the safety of the Mobile Agent during the phase of transit. Since Mobile Agents are capable of deciding their itinerary dynamically, a decision support system which helps to ensure the trustworthiness of a platform would complement the decision. A Trust Scoring System is therefore proposed to measure the trustworthiness of a platform based on a metric termed Trust Score. Trust Score varies dynamically with respect to time and is based on a function comprising of five parameters namely Persistence, Competence, Reputation, Credibility and Integrity. In order to reduce the computational latency, another metric named Trust Rank for platforms, based on Trustability co-efficient of variation is introduced. The experimentation is done in cloud environment with platforms located at different geographic regions. The performance is evaluated in terms of response time and accuracy of decision. From the experimental results, it is evident that the Trust Ranking mechanism consumes less response time and improves the accuracy of decision of Mobile Agents during their itineraries, compared to that of the prototype system that uses Trust Score alone as a measure of decision-making.
Natural Language Processing (NLP) empowered mobile computing is the use of NLP techniques in the context of mobile environment. Research in this field has drawn much attention given the continually increasing number of publications in the last five years. This study presents the status and development trend of the research field through an objective, systematic, and comprehensive review of relevant publications available from Web of Science. Analysis techniques including a descriptive statistics method, a geographic visualization method, a social network analysis method, a latent dirichlet allocation method, and an affinity propagation clustering method are used. We quantitatively analyze the publications in terms of statistical characteristics, geographical distribution, cooperation relationship, and topic discovery and distribution. This systematic analysis of the field illustrates the publications evolution over time and identifies current research interests and potential directions for future research. Our work can potentially assist researchers in keeping abreast of the research status. It can also help monitoring new scientific and technological development in the research field.
We consider decision problems that are solved in a distributed fashion by synchronous mobile agents operating in an unknown, anonymous network. Each agent has a unique identifier and an input string and they have to decide collectively a property which may involve their input strings, the graph on which they are operating, and their particular starting positions. Building on recent work by Fraigniaud and Pelc [J. Parallel Distrib. Comput, vol. 109, pp. 117–128], we introduce several natural new computability classes allowing for a finer classification of problems below MAV or its complement class co-MAV, the former being the class of problems that are verifiable when the agents are provided with an appropriate certificate. We provide inclusion and separation results among all these classes. We also determine their closure properties with respect to set-theoretic operations. Our main technical tool, which is of independent interest, is a new meta-protocol that enables the execution of a possibly infinite number of mobile agent protocols essentially in parallel, similarly to the well-known dovetailing technique from classical computability theory.
In this paper, we consider the uniform deployment problem of mobile agents in asynchronous unidirectional rings, which requires the agents to uniformly spread in the ring. The uniform deployment problem is in striking contrast to the rendezvous problem which requires the agents to meet at the same node. While rendezvous aims to break the symmetry, uniform deployment aims to attain the symmetry. It is well known that the symmetry breaking is difficult in distributed systems and the rendezvous problem cannot be solved from some initial configurations. Hence, we are interested in clarifying what difference the uniform deployment problem has on the solvability and the number of agent moves compared to the rendezvous problem. We consider two problem settings, with knowledge of k (or n) and without knowledge of k or n where k is the number of agents and n is the number of nodes. First, we consider agents with knowledge of k (or n since k andn can be easily obtained if one of them is given). In this case, we propose two algorithms. The first algorithm solves the uniform deployment problem with termination detection. This algorithm requires O(klogn) memory space per agent, O(n) time, and O(kn) total moves. The second algorithm also solves the uniform deployment problem with termination detection. This algorithm reduces the memory space per agent to O(logn), but uses O(nlogk) time, and requires O(kn) total moves. Both algorithms are asymptotically optimal in terms of total moves since there are some initial configurations such that agents require Ω(kn) total moves to solve the problem. Next, we consider agents with no knowledge of k or n. In this case, we show that, when termination detection is required, there exists no algorithm to solve the uniform deployment problem. For this reason, we consider the relaxed uniform deployment problem that does not require termination detection, and we propose an algorithm to solve the relaxed uniform deployment problem. This algorithm requires O((k∕l)log(n∕l)) memory space per agent, O(n∕l) time, and O(kn∕l) total moves when the initial configuration has symmetry degree l. This means that the algorithm can solve the problem more efficiently when the initial configuration has higher symmetric degree (i.e., is closer to uniform deployment). Note that all the proposed algorithms achieve uniform deployment from any initial configuration, which is a striking difference from the rendezvous problem because the rendezvous problem is not solvable from some initial configurations.
This chapter proposes the agent‐oriented paradigm for the modeling and implementation of body sensor networks (BSNs). After introducing background concepts on the agent‐computing paradigm and, specifically, on software agents in the wireless sensor network (WSN) context, the chapter discusses motivations and challenges on the exploitation of agents for BSNs and provides a description of the related state‐of‐the‐art. The chapter then presents agent‐based modeling and implementation of BSNs. Furthermore, the chapter discusses related work and a qualitative comparison among the most diffused (mobile) agent platforms for WSNs. Finally, it focuses on agent‐oriented BSN application development based on Mobile Agent Platform for Sun SPOT (MAPS). Specifically, a MAPS‐based human activity recognition BSN system, and main components of the MAPS architecture: mobile agent, mobile agent execution engine, mobile agent migration manager, mobile agent communication channel, mobile agent naming, timer manager and resource manager are described.
Edge computing in Internet of Things enhances application execution by retrieving cloud resources to the close proximity of resource-constrained end devices at the edge and by enabling task offloading from end devices to the edge. In this paper, edge computing platforms are extended into the data producing end devices, including wireless sensor network nodes and smart-phones, with mobile agents. Mobile agents operate as a multi-agent system on the opportunistic network of heterogeneous end devices, where the benefits include autonomous, asynchronous and the adaptive execution and relocation of application-specific tasks, while taking into account local resource availability. In addition to the vertical edge connectivity, mobile agents enable horizontal sharing of the information between end devices. Use cases are presented, where mobile agents address challenges in current edge computing platforms. An edge application is evaluated, where mobile agents as a multi-agent system process sensor data in a heterogeneous set of end devices, control the operation of the devices and share their results with system components. Mobile agents operate atop a REST-based mobile agent software framework that relies on embedded Web services for interoperability. A real-world evaluation and large-scale simulations show that energy consumption is reduced significantly in the edge application execution.
In this paper, we propose a new class of service called server migration service (SMS) to augment the existing IaaS (Infrastructure as a Service). SMS allows servers (server-side processes of a network application) to dynamically and automatically migrate as their clients (client-side processes of a network application) change their locations in order to reduce the total monetary penalty that the SMS provider pays to its SMS subscribers when failing to provide them with the guaranteed level of QoS. In this paper, we consider the monetary impact that arises from QoS degradation due to server migration and build an integer programming model to determine when and to which location servers should migrate to minimize the total monetary penalty incurred by the SMS provider. Numerical examples show that SMS achieves up to 96% lower total monetary penalty compared to that without server migration. Numerical examples also show that the integer programming model developed in this paper requires reasonable computation time under realistic parameter settings.
Programming and Deploying Java Mobile Agents with Aglets Danny B. Lange (danny@genmagic.com) is director of agent technology in General Magic, Inc. in Sunnyvale, Calif. Mitsuru Oshima (oshima@genmagic.com) is a technical lead in General Magic
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Lange, D., and Oshima, M. Programming and Deploying Java Mobile Agents with Aglets. Addison-Wesley Longman, Reading, Mass., 1998. Danny B. Lange (danny@genmagic.com) is director of agent technology in General Magic, Inc. in Sunnyvale, Calif. Mitsuru Oshima (oshima@genmagic.com) is a technical lead in General Magic, Inc. in Sunnyvale, Calif. © 1999 ACM 0002-0782/99/0300 $5.00