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Search and replication in unstructured peer-to-peer networks
... In random walk based algorithm as name suggest the query node is send by query packets in random fashion until the target is achieved [8] . ...
... Biased Random walk [3]uses statistical preferences .This algorithms can reduce network traffic and enhance the system scalability but disadvantage is that it usually result in much longer search latency [7], [8]. Puttaswamy et al proposed to use index replication [8] to find "rare" objects. ...
... Biased Random walk [3]uses statistical preferences .This algorithms can reduce network traffic and enhance the system scalability but disadvantage is that it usually result in much longer search latency [7], [8]. Puttaswamy et al proposed to use index replication [8] to find "rare" objects. By using this every node stores just the metadata of its data on all of its multihop neighbors. ...
The Peer to peer architecture run over internet are widely used in unstructured topology. Random walk based and control flooding resource query algorithms are widely used in peer to peer network. In this paper we consider searching of file in ad hoc network. We propose Enhanced Selective Dynamic Query algorithm. The main aim of this algorithm is to minimize traffic cost and response latency for resource query response. When user want to search a query first history table is referred. If query is present in history table next searching is not required otherwise optimal combination of integer TTL value and set of neighbor for next query round is calculated in network by using knapsack for next query. This algorithm tries to achieve best tradeoff between traffic cost and response latency.
... This abstract problem naturally captures-and is directly motivated by-several important real-life networking applications. These include content and information-centric networks (CCNs/ICNs) [22,32,33], core and edge content delivery networks (CDNs) [7,13], micro/femtocell networks [34], and peer-to-peer networks [28], to name a few. For example, in hierarchical CDNs, requests for content can be served by intermediate caches placed at the network's edge, e.g., within the same administrative domain (e.g., AS or ISP) as the originator of the request; if, however, content is not cached locally, the request can be forwarded to a core server, that acts as a cache of last resort. ...
... A simple, elegant algorithm that attains both properties, and is often encountered in the literature of the different applications mentioned above, is path replication [10,12,22,25,28,33,39]. Cast in the context of our problem, the algorithm roughly proceeds as follows: when an item traverses the reverse path towards a node that requested it, it is cached by every intermediate node encountered. ...
We study the problem of optimal content placement over a network of caches, a problem naturally arising in several networking applications, including ICNs, CDNs, and P2P systems. Given a demand of content request rates and paths followed, we wish to determine the content placement that maximizes the expected caching gain, i.e., the reduction of routing costs due to intermediate caching. The offline version of this problem is NP-hard and, in general, the demand and topology may be a priori unknown. Hence, a distributed, adaptive, constant approximation content placement algorithm is desired. We show that path replication, a simple algorithm frequently encountered in literature, can be arbitrarily suboptimal when combined with traditional eviction policies, like LRU, LFU, or FIFO. We propose a distributed, adaptive algorithm that performs stochastic gradient ascent on a concave relaxation of the expected caching gain, and constructs a probabilistic content placement within 1-1/e factor from the optimal, in expectation. Motivated by our analysis, we also propose a novel greedy eviction policy to be used with path replication, and show through numerical evaluations that both algorithms significantly outperform path replication with traditional eviction policies over a broad array of network topologies.
... In addition, every cache with a lower retrieval cost performs an eviction according to the corresponding policy under a cache hit scenario. This corresponds to the popular path replication algorithm [19,32], equipped with LRU or LFU, applied to our setting. • Online slot-fairness (OSF) policy: an instance of OHF in Algorithm 1 configured with a dual (conjugate) subspace Θ = {(−1) ∈I } (i.e., taking → 0) comprised of a single point. ...
... Thus, Eq.(19) and Eq.(20) give W T = ( ). We provide a simple example of such an adversary. ...
We study the fairness of dynamic resource allocation problem under the -fairness criterion. We recognize two different fairness objectives that naturally arise in this problem: the well-understood slot-fairness objective that aims to ensure fairness at every timeslot, and the less explored horizon-fairness objective that aims to ensure fairness across utilities accumulated over a time horizon. We argue that horizon-fairness comes at a lower price in terms of social welfare. We study horizon-fairness with the regret as a performance metric and show that vanishing regret cannot be achieved in presence of an unrestricted adversary. We propose restrictions on the adversary's capabilities corresponding to realistic scenarios and an online policy that indeed guarantees vanishing regret under these restrictions. We demonstrate the applicability of the proposed fairness framework to a representative resource management problem considering a virtualized caching system where different caches cooperate to serve content requests.
... To prevent flooding of the network, Freenet mandates that each query be associated with a Time To Live (TTL). In addition, Subsequent changes to the algorithm have been proposed by (Lv, Cao, Cohen, Li, and Shenker 2002), which substitute flooding by a set of random walkers. ...
... The simulation based study described in (Lv, Cao, Cohen, Li, and Shenker 2002) demonstrates marked improvement in performance. However, subsequent studies (Ritter 2001 ) have demonstrated that the Gnutella approach remains non-scalable. ...
p>An emergent trend in large scale distributed systems enables collaboration between large numbers of independent resource providers. Grid computing and peer-to-peer computing are part of this trend. Resource management in such systems is inherently different from that found in traditional distributed systems, the key difference being that the new classes of systems are primarily designed to operate under inconsistent system information and temporally varying operating environments. Although primarily used to enable collaboration of computational resources, these systems have also found application in the field of distributed data management. Although the principles of grid computing and peer-to-peer computing have found many applications, little effort has been made to abstract the common requirements, in order to provide a conceptual resource framework. This thesis investigates the alleviation of such common requirements through investigations in the field of online scheduling, information dissemination in peer-to-peer networks, and query processing in distributed stream processing systems.
A survey of system types is provided to highlight the new trends observed. A top down approach to developing a unifying model seems inapplicable and the range of problems encountered in these system types can only be addressed by identifying common trends and addressing them individually. Consequently, three application domains have been identified in the respective fields of online scheduling, data dissemination and stream query processing. Each of these application class is investigated individually. For each application domain, a review of the state-of-the-art is followed by a precise definition of the problem addressed in the application domain and the solutions developed are substantiated with experimental evaluation. Findings from individual applications have been summarized to generalize the observations towards an overall hypothesis.</p
... In contrast, if one does not have any information about network structure or has only local information (such as the degrees of neighbors), RWs provide a viable approach for searching in networks. One context in which this idea has been investigated and implemented are decentralized peer-to-peer networks [273,274]. A node that sends a query emits N rw packets to neighbors selected uniformly at random. ...
... Therefore, there is a trade-off between search overhead and search efficiency. RW search methods are comparable with flooding search methods in various networks and scenarios [273]. In a flooding method, first used by Gnutella, a node with a query asks all of its neighbors, each of which in turn asks all of its unvisited neighbors, and so on [275]. ...
In this article, we study a class of random walk (RW) problem for fixed, random, linearly decreasing and geometrically shrinking step sizes and find that they all obey dynamic scaling which we verified using the idea of data-collapse. We show that the full width at half maximum (FWHM) of the probability density P(x, t) curves is equivalent to the root-mean square (rms) displacement which grows with time as x rms ∼ t α/ 2 and the peak value of P(x, t) at x = 0 decays following a power-law P max ∼ t −α/ 2 with α = 1 in all cases but one. In the case of geometrically shrinking steps, where the size of the n th step is chosen to be R n n , with R n being the n th largest number among N random numbers drawn within [0,1], we find α = 1 / 2. Such non-linear relation between mean squared displacement and time x 2 ∼ t α with α = 1 / 2 instead of α = 1 suggests that the corresponding Brownian motion describes sub-diffusion.
... The number of hops taken to find the resource is called the search length of that walk. The performance of this direct application of random walks to network search has been studied in [1,2,3,4,5]. ...
Random walks can be used to search complex networks for a desired resource. To reduce search lengths, we propose a mechanism based on building random walks connecting together partial walks (PW) previously computed at each network node. Resources found in each PW are registered. Searches can then jump over PWs where the resource is not located. However, we assume that perfect recording of resources may be costly, and hence, probabilistic structures like Bloom filters are used. Then, unnecessary hops may come from false positives at the Bloom filters. Two variations of this mechanism have been considered, depending on whether we first choose a PW in the current node and then check it for the resource, or we first check all PWs and then choose one. In addition, PWs can be either simple random walks or self-avoiding random walks. Analytical models are provided to predict expected search lengths and other magnitudes of the resulting four mechanisms. Simulation experiments validate these predictions and allow us to compare these techniques with simple random walk searches, finding very large reductions of expected search lengths.
... С точки зрения структуры одноранговые децентрализованные сети делятся на две основные категории: структурированные и неструктурированные [19,20,21,22]. В структурированных сетях P2P, таких, например, как Chord [23], точно определены и сетевая архитектура и размещение данных. ...
The paper presents a comparative overview of decentralized data storages of various types. It is shown that although they have a number of common properties that are typical of all peer-to-peer (P2P) networks, the problems to be solved and, accordingly, the technologies used to build different types of storages differ significantly.
... Since there is no particular keying or organization of the content, the search techniques are typically based on flooding. Thus, the searches may take very long time for rare items, though popular items can be found very fast due to possible leveraging of locality of reference [37] and caching/replication [13]. ...
Several protocol efficiency metrics (e.g., scalability, search success rate, routing reachability and stability) depend on the capability of preserving structure even over the churn caused by the ad-hoc nodes joining or leaving the network. Preserving the structure becomes more prohibitive due to the distributed and potentially uncooperative nature of such networks, as in the peer-to-peer (P2P) networks. Thus, most practical solutions involve unstructured approaches while attempting to maintain the structure at various levels of protocol stack. The primary focus of this paper is to investigate construction and maintenance of scale-free topologies in a distributed manner without requiring global topology information at the time when nodes join or leave. We consider the uncooperative behavior of peers by limiting the number of neighbors to a pre-defined hard cutoff value (i.e., no peer is a major hub), and the ad-hoc behavior of peers by rewiring the neighbors of nodes leaving the network. We also investigate the effect of these hard cutoffs and rewiring of ad-hoc nodes on the P2P search efficiency.
... In all the experiments we present in this paper, the number of nodes in the network is 1024, each individually deciding how to distribute its incoming content requests across the replica nodes. We use both Poisson and Pareto request inter-arrival distributions, both of which have been found to hold in peer-to-peer networks [Cao02], [Mar02]. ...
This paper studies the problem of load-balancing the demand for content in a peer-to-peer network across heterogeneous peer nodes that hold replicas of the content. Previous decentralized load balancing techniques in distributed systems base their decisions on periodic updates containing information about load or available capacity observed at the serving entities. We show that these techniques do not work well in the peer-to-peer context; either they do not address peer node heterogeneity, or they suffer from significant load oscillations. We propose a new decentralized algorithm, Max-Cap, based on the maximum inherent capacities of the replica nodes and show that unlike previous algorithms, it is not tied to the timeliness or frequency of updates. Yet, Max-Cap can handle the heterogeneity of a peer-to-peer environment without suffering from load oscillations.
... Recently Peer-to-Peer (P2P) systems have emerged as a new distributed computing paradigm. Three major models have rapidly emerged: centralised, decentralised structured and decentralised unstructured [1]. The centralised model, such as Napster [2] and Bittorent [3], uses a central server to index the content and the peers. ...
In this paper we proposed a hierarchical P2P network based on a dynamic partitioning on a 1-D space. This hierarchy is created and maintained dynamically and provides a gridmiddleware (like DGET) a P2P basic functionality for resource discovery and load-balancing.This network architecture is called TreeP (Tree based P2P network architecture) and is based on atessellation of a 1-D space. We show that this topology exploits in an efficient way theheterogeneity feature of the network while limiting the overhead introduced by the overlaymaintenance. Experimental results show that this topology is highly resilient to a large number ofnetwork failures.
... The focus of this paper is on random walks in networks, in particular, decentralized algorithms for performing random walks in arbitrary networks. Random walks are used as an integral subroutine in a wide variety of network applications ranging from token management [32,8,14], load balancing [34], small-world routing [40], search [56,1,12,29,43], information propagation and gathering [9,37], network topology construction [29,41,42], checking expansion [22], constructing random spanning trees [10,6,5], monitoring overlays [48], group communication in ad-hoc network [21], gathering and dissemination of information over a network [3], distributed construction of expander networks [41], and peer-to-peer membership management [26,57]. Random walks are also very useful in providing uniform and efficient solutions to distributed control of dynamic networks [11,56]. ...
Performing random walks in networks is a fundamental primitive that has found applications in many areas of computer science, including distributed computing. In this paper, we focus on the problem of sampling random walks efficiently in a distributed network and its applications. Given bandwidth constraints, the goal is to minimize the number of rounds required to obtain random walk samples. All previous algorithms that compute a random walk sample of length as a subroutine always do so naively, i.e., in rounds. The main contribution of this paper is a fast distributed algorithm for performing random walks. We present a sublinear time distributed algorithm for performing random walks whose time complexity is sublinear in the length of the walk. Our algorithm performs a random walk of length in rounds ( hides \polylog{n} factors where n is the number of nodes in the network) with high probability on an undirected network, where D is the diameter of the network. For small diameter graphs, this is a significant improvement over the naive bound. Furthermore, our algorithm is optimal within a poly-logarithmic factor as there exists a matching lower bound [Nanongkai et al. PODC 2011]. We further extend our algorithms to efficiently perform k independent random walks in rounds. We also show that our algorithm can be applied to speedup the more general Metropolis-Hastings sampling. Our random walk algorithms can be used to speed up distributed algorithms in applications that use random walks as a subroutine, such as computing a random spanning tree and estimating mixing time and related parameters. Our algorithm is fully decentralized and can serve as a building block in the design of topologically-aware networks.
... While we make the assumption of fixed chunk size here to simplify the problem formulation, all results in this paper can be easily extended to variable chunk sizes. Nevertheless, fixed chunk sizes are indeed used by many existing storage systems[55][56][57]. ...
Modern distributed storage systems often use erasure codes to protect against disk and node failures to increase reliability, while trying to meet the latency requirements of the applications and clients. Storage systems may have caches at the proxy or client ends in order to reduce the latency. In this paper, we consider a novel caching framework with erasure code called functional caching. Functional Caching involves using erasure-coded chunks in the cache such that the code formed by the chunks in storage nodes and cache combined are maximal-distance-separable (MDS) erasure codes. Based on the arrival rates of different files, placement of file chunks on the servers, and service time distribution of storage servers, an optimal functional caching placement and the access probabilities of the file request from different disks are considered. The proposed algorithm gives significant latency improvement in both simulations and a prototyped solution in an open-source, cloud storage deployment.
... In this paper, in contrast, we propose the use of random walks. Random walks are as simple as flooding, and lead to reduced congestion [17,10,18,19] while still taking advantage of spacial and temporal locality [20,15]. ...
Content distribution networks have been extremely successful in today's Internet. Despite their success, there are still a number of scalability and performance challenges that motivate clean slate solutions for content dissemination, such as content centric networking. In this paper, we address two of the fundamental problems faced by any content dissemination system: content search and content placement. We consider a multi-tiered, multi-domain hierarchical system wherein random walks are used to cope with the tradeoff between exploitation of known paths towards custodians versus opportunistic exploration of replicas in a given neighborhood. TTL-like mechanisms, referred to as reinforced counters, are used for content placement. We propose an analytical model to study the interplay between search and placement. The model yields closed form expressions for metrics of interest such as the average delay experienced by users and the load placed on custodians. Then, leveraging the model solution we pose a joint placement-search optimization problem. We show that previously proposed strategies for optimal placement, such as the square-root allocation, follow as special cases of ours, and that a bang-bang search policy is optimal if content allocation is given.
... Data Sharing, as a pivotal mechanism that integrates distributed data of multi-parties in networks to provide better data content services, has garnered persistent attention in the fields of networking and distributed systems. In traditional overlay networks, data sharing is achieved via various forms of indexing mechanisms, which can be divided into local indexing, centralized indexing, and distributed indexing [4]- [6]. Here, we mainly focus on the distributed ways represented by Distributed Hash Tables (DHTs) [6]. ...
Edge storage promises to be crucial for edge computing infrastructure, which enables users to access data within a low delay from widespread storage nodes at the network edge. The key challenge is how to integrate massive geographically distributed weak edge nodes to form an efficient storage system, enabling users to launch data operations from any node or retrieve the desired data across the entire distributed system. To address this data-sharing problem, researchers from both the traditional peer-to-peer (P2P) overlay networking and emerging edge computing fields have proposed some decentralized indexing mechanisms. However, existing studies lack insightful descriptions and analyses about the nature of the data-sharing problem at the network edge. It motivates us to rethink the edge data-sharing framework and provide the problem reformulation for analyzing the limitations of existing schemes. We reveal that the existing data-sharing schemes fail in complex network topologies which can be regarded as high-dimensional network spaces beyond the representation of low-dimensional Euclidean spaces or other existing hash spaces. A better space abstraction is an urgent need to alleviate the performance degradation due to the dimensional mismatch between network spaces and virtual spaces. To fill this gap, this paper proposes the Kautz metric space, a novel space abstraction extended from Kautz graphs, where the coordinates and the metric are defined as Kautz strings and Kautz distances (i.e. the shortest distances in undirected Kautz graphs), respectively. We design a dynamic programming algorithm to directly compute the Kautz distances. Then, we propose KMSharing, an efficient edge data-sharing scheme: both nodes and data are represented in a Kautz metric space, where the Kautz distance of any two Kautz strings reflects the network delay of the corresponding nodes. The workflow of KMSharing consists of three core components: the virtual address allocation represents edge nodes in the Kautz metric space; the data-to-node mapping ensures the uniqueness of target nodes; and forwarding table construction ensures the data delivery. Theoretical analyses confirm that KMSharing ideally achieves
\Ocal{\tau}
network delays,
\Ocal{\log N}
overlay hops, and
\Ocal{1}
forwarding entries in an
N
-node edge system with the network radius
, while the successive ensuring data delivery. Its worst-case network delay
\Ocal{\tau\log N}
is also much better than
\Ocal{\tau N^\alpha},\alpha\mathrm{\in}(0,1)
, the worst case of the baselines using Euclidean spaces. Evaluation on various network topologies also shows that our KMSharing effectively reduces network delays and indexing costs than existing data-sharing schemes.
... P2P networks facilitate data-sharing and communication across systems, even ones that may otherwise be incompatible or isolated, by relying on open technologies and standard protocols. P2P networks facilitate cooperation between stakeholders and organizations by removing these data barriers [108]. Another crucial component of P2P networks is transparency. ...
Recently, there has been more interest in Decentralized Data-Sharing (DDS) because of the introduction of Dataspace 4.0. DDS is becoming increasingly popular as a safe, open, and effective way for many parties to data-sharing. Unlike conventional, centralized methods, DDS has several benefits, such as better knowledge exchange, higher accessibility and interoperability, and data privacy and security. The paper covers DDS's advantages, including improved resilience, higher security, increased privacy, and improved interoperability. DDS gives people and organizations more control and ownership over their data while reducing the dangers of centralized data management. In this survey, we highlight promising technologies for DDS in Dataspace 4.0, including Federated Learning (FL), blockchain, decentralized file systems, semantic web and knowledge representation, and Peer-to-Peer (P2P) networks. We highlight the challenges, opportunities, and future directions of technology enabling further DDS advancement in Industry 4.0. INDEX TERMS Industry 4.0, P2P network, Dataspace, federated learning, Dataspace 4.0, decentralized data-sharing, blockchain, decentralized file systems, semantic web
... This is the author's version which has not been fully edited and content may change prior to final publication. P2P networks facilitate cooperation between stakeholders and organizations by removing these data barriers [108]. Another crucial component of P2P networks is transparency. ...
Recently, there has been more interest in Decentralized Data-Sharing (DDS) because of the introduction of Dataspace 4.0. DDS is becoming increasingly popular as a safe, open, and effective way for many parties to data-sharing. Unlike conventional, centralized methods, DDS has several benefits, such as better knowledge exchange, higher accessibility and interoperability, and data privacy and security. The paper covers DDS’s advantages, including improved resilience, higher security, increased privacy, and improved interoperability. DDS gives people and organizations more control and ownership over their data while reducing the dangers of centralized data management. In this survey, we highlight promising technologies for DDS in Dataspace 4.0, including Federated Learning (FL), blockchain, decentralized file systems, semantic web and knowledge representation, and Peer-to-Peer (P2P) networks. We highlight the challenges, opportunities, and future directions of technology enabling further DDS advancement in Industry 4.0.
... The fact that a random walk visits every vertex of a connected, undirected graph in polynomial time was first used to solve the undirected s − t connectivity problem in logarithmic space [4]. Since then random walks have become a fundamental primitive in the design of randomised algorithms which feature in approximation algorithms and sampling [44,57], load balancing [35,59], searching [25,45], resource location [36], property testing [15,38,39], graph parameter estimation [7,14] and biological applications [8,10,27]. ...
Random walks on graphs are an essential primitive for many randomised algorithms and stochastic processes. It is natural to ask how much can be gained by running k multiple random walks independently and in parallel. Although the cover time of multiple walks has been investigated for many natural networks, the problem of finding a general characterisation of multiple cover times for worst-case start vertices (posed by Alon, Avin, Koucký, Kozma, Lotker and Tuttle in 2008) remains an open problem. First, we improve and tighten various bounds on the stationary cover time when k random walks start from vertices sampled from the stationary distribution. For example, we prove an unconditional lower bound of on the stationary cover time, holding for any n -vertex graph G and any . Secondly, we establish the stationary cover times of multiple walks on several fundamental networks up to constant factors. Thirdly, we present a framework characterising worst-case cover times in terms of stationary cover times and a novel, relaxed notion of mixing time for multiple walks called the partial mixing time . Roughly speaking, the partial mixing time only requires a specific portion of all random walks to be mixed. Using these new concepts, we can establish (or recover) the worst-case cover times for many networks including expanders, preferential attachment graphs, grids, binary trees and hypercubes.
... The data sharing service has been extensively researched in overlay networks to quickly locate required data items, via many indexing mechanisms, such as the local index, centralized index, and distributed index [26]- [28]. For those distributed indexing mechanisms like Distributed Hash Tables (DHTs) [28], the high latency is their key problem. ...
... In transportation [60], it can assist in measuring changes in the mobility patterns of groups of individuals. Moreover, this methodology can be employed in engineering to track groups of devices engaged in communication and collaboration within distributed applications, such as fleets of unmanned vehicles or wireless sensor networks [61][62][63]. Importantly, this approach holds broader applicability in studying the evolution of phenomena where groups of elements undergo temporal changes. For example, in the realm of language evolution [64,65], our method can provide insights into how groups of words may initially exhibit proximity but gradually disperse into different clusters as the language evolves, which can add a temporal dimension to natural language processing analysis. ...
The interactions between individuals play a pivotal role in shaping the structure and dynamics of social systems. Complex network models have proven invaluable in uncovering the underlying mechanisms that govern the formation and evolution of these systems. However, conventional network representations primarily emphasize pairwise interactions, represented as edges in the network. In reality, many social interactions occur within groups rather than individual pairs. To capture this crucial aspect, higher-order network representations come into play, especially to describe those complex systems that are inherently composed of agents interacting with group dynamics. Despite recent research advancements in exploring temporal higher-order networks in various systems, our understanding of collaboration networks remains limited. Specifically, there is a lack of knowledge regarding the patterns of group interactions within scientific collaborations. How do groups form and evolve in this context? In this study, we aim to delve into the temporal properties of groups within collaboration networks. Our investigation focuses on uncovering the mechanisms that govern the global, group, and individual-level dynamics, shedding light on how individuals collaborate and how groups form and disband over time. By studying these temporal patterns, we take a significant stride forward in comprehending the intricate dynamics of higher-order interactions within human collaboration systems.
... Moreover, all caches with a lower retrieval cost update their state as if a miss occurred locally. This corresponds to the popular path replication algorithm [21,35], equipped with LRU or LFU, adapted to our setting. • Online slot-fairness (OSF) policy. ...
We study the fairness of dynamic resource allocation problem under the α-fairness criterion. We recognize two different fairness objectives that naturally arise in this problem: the well-understood slot-fairness objective that aims to ensure fairness at every timeslot, and the less explored horizon-fairness objective that aims to ensure fairness across utilities accumulated over a time horizon. We argue that horizon-fairness comes at a lower price in terms of social welfare. We study horizon-fairness with the regret as a performance metric and show that vanishing regret cannot be achieved in presence of an unrestricted adversary. We propose restrictions on the adversary's capabilities corresponding to realistic scenarios and an online policy that indeed guarantees vanishing regret under these restrictions. We demonstrate the applicability of the proposed fairness framework to a representative resource management problem considering a virtualized caching system where different caches cooperate to serve content requests.
... 1) Uninformed Message Forwarding: Uninformed routing algorithms is a forwarding protocol mechanism that does not use the knowledge of query semantics or destination node's address in the forwarding decisions. In this direction, flooding [65] and random walk [66] are the most popular algorithms. These algorithms can be used to flood the message in the network so that network elements can examine the message and apply the required computation in the case that they can implement the computation. ...
In comparison with cloud computing, edge computing offers processing at locations closer to end devices and reduces the user experienced latency. The new recent paradigm of innetwork computing employs programmable network elements to compute on the path and prior to traffic reaching the edge or cloud servers. It advances common edge/cloud server based computing through proposing line rate processing capabilities at closer locations to the end devices. This paper discusses use cases, enabler technologies and protocols for in-network computing. According to our study, considering programmable data plane as an enabler technology, potential in-network computing applications are in-network analytics, in-network caching, innetwork security, and in-network coordination. There are also technology specific applications of in-network computing in the scopes of cloud computing, edge computing, 5G/6G, and NFV. In this survey, the state of the art, in the framework of the proposed categorization, is reviewed. Furthermore, comparisons are provided in terms of a set of proposed criteria which assess the methods from the aspects of methodology, main results, as well as application-specific criteria. Finally, we discuss lessons learned and highlight some potential research directions.
... As reported in the [18,19], some files are very popular in P2P networks whereas some are rarely accessed. The popularity of a file is judged on the basis of number of access of that file. ...
A P2P (peer-to-peer) network is a distributed system dependent on the IP-based networks, where independent nodes join and leave the network at their drive. The files (resource) are shared in distributed manner and each participating node ought to share its resources. Some files in P2P networks are accessed frequently by many users and such files are called popular files. Replication of popular files at different nodes in structured P2P networks provides significant reduction in resource lookup cost. Most of the schemes for resource access in the structured P2P networks are governed by DHT (Distributed Hash Table) or DHT-based protocols like Chord. Chord protocol is well accepted protocol among structured P2P networks due to its simple notion and robust characteristics. But Chord or other resource access protocols in structured P2P networks do not consider the cardinality of replicated files to enhance the lookup performance of replicated files. In this paper, we have exploited the cardinality of the replicated files and proposed a resource cardinality-based scheme to enhance the resource lookup performance in the structured P2P networks. We have also proposed the notion of trustworthiness factor to judge the reliability of a donor node. The analytical modelling and simulation analysis indicate that the proposed scheme performs better than the existing Chord and PCache protocols.
... P2P networks have a variety of topologies, communication patterns between nodes, and types of nodes that participate. Predominantly, there are three main categories of network topologies, which are centralized, decentralized structured, and decentralized unstructured [35]. ...
Blockchain technology is a highly regarded technology that possesses a plethora of exciting features. This paper analyzes trends and highlights the potential benefits of blockchain deployment in IoT and healthcare. According to the literature, blockchain technology is mostly utilized for data management operations in healthcare and IoT, specifically to improve data security, which includes data integrity, access control, and privacy preservation. In both areas, six distinct types of data security preservation strategies are applied. Additionally, publications highlight how blockchain and IoT, including health IoT, can be used in an integrative way. Three integration mechanisms were seen to accomplish this goal. These solutions range from fully integrating blockchain into data exchanges between IoT devices to using it solely for metadata storage. The most frequently covered area of IoT is a smart city, where blockchain is utilized to improve real-time data sharing, and electricity trading, and so on. Additionally, it is learned that, despite the numerous benefits of blockchain in healthcare, authors typically use it for drug supply chain management and data management purposes in order to avoid counterfeiting and empower patients with regard to their data, respectively.
... Searching in P2P systems has been achieved by two techniques Blind search and Informed search. These search techniques relied on various query mechanisms in unstructured P2P systems, such as gossiping [13][14][15], random walk [16,17], k-walker [16,18], controlled flooding, and pure flooding [19]. Among these, gossiping is an attractive and widely adopted mechanism for modern query routing approaches [15,20]. ...
... Quantum walks are the quantum counterpart of the Classical random walks (CRWs), which are employed to model phenomena as chemical reactions [41,53,81], genetic sequence location [80,54,63], optimal search strategies [56,15,67], diffusion and mobility in materials [52,38,79], exchange rate forecasts in economical sciences [57,18,51] and information spreading in complex networks [66,64,71]. Furthermore, they can successfully implement efficient algorithms, for example they can solve differential equations [3,47], optimization [15,16] and clustering problems [69,82]. ...
This manuscript gathers and subsumes a long series of works on using QW to simulate transport phenomena. Quantum Walks (QWs) consist of single and isolated quantum systems, evolving in discrete or continuous time steps according to a causal, shift-invariant unitary evolution in discrete space. We start reminding some necessary fundamentals of linear algebra, including the definitions of Hilbert space, tensor state, the definition of linear operator and then we briefly present the principles of quantum mechanics on which this thesis is grounded. After having reviewed the literature of QWs and the main historical approaches to their study, we then move on to consider a new property of QWs, the plasticity. Plastic QWs are those ones admitting both continuous time-discrete space and continuous spacetime time limit. We show that such QWs can be used to quantum simulate a large class of physical phenomena described by transport equations. We investigate this new family of QWs in one and two spatial dimensions, showing that in two dimensions, the PDEs we can simulate are more general and include dispersive terms. We show that the above results do not need to rely on the grid and we prove that such QW-based quantum simulators can be defined on 2-complex simplicia, i.e. triangular lattices. Finally, we extend the above result to any arbitrary triangulation, proving that such QWs coincide in the continuous limit to a transport equation on a general curved surface, including the curved Dirac equation in 2+1 spacetime dimensions.
... balancing in cluster-based applications: choosing a host at random among those that are available is often a choice that provides performance close to that offered by more complex selection criteria, without imposing any burden [1]. Another case where having access to random node identifiers is important is epidemic-based applications: by periodically selecting few random nodes as neighbours, large-scale environments preserve their connectivity despite node dynamicity [2][3][4][5]. ...
We consider the problem of achieving uniform node sampling in large scale systems in presence of Byzantine nodes. This service offers a single simple primitive that returns, upon invocation, the identifier of a random node that belongs to the system. We first propose an omniscient strategy that processes on the fly an unbounded and arbitrarily biased input stream made of node identifiers exchanged within the system, and outputs a stream that preserves the uniformity property (same probability to appear in the sample). We show that this property holds despite any arbitrary bias introduced by the adversary. We then propose a strategy that is capable of approximating the omniscient strategy without requiring any prior knowledge on the composition of the input stream. We show through both theoretical analysis and extensive simulations that this strategy accurately approximates the omniscient one. We evaluate the resilience of the strategy by studying two representative attacks. We quantify the minimum number of identifiers that Byzantine nodes must insert in the input stream to prevent uniformity. Finally, we propose a new construction in series that allows to both increase the accuracy of a single sketch and decrease the time to converge to a uniform output stream.
... These utility functions are known to yield two important notions of fairness, proportional fairness and minimum potential delay fairness, respectively (see Table 4). In addition, we also consider the cube root utility, which yields the square root allocation that has already been shown to be of interest in the context of ICN [27] and peer-to-peer systems [22,40]. ...
Caching is a fundamental element of networking systems since the early days of the Internet. By filtering requests toward custodians, caches reduce the bandwidth required by the latter and the delay experienced by clients. The requests that are not served by a cache, in turn, comprise its miss stream. We refer to the dependence of the cache state and miss stream on its history as hysteresis. Although hysteresis is at the core of caching systems, a dimension that has not been systematically studied in previous works relates to its impact on caching systems between misses, evictions, and insertions.
In this article, we propose novel mechanisms and models to leverage hysteresis on cache evictions and insertions. The proposed solutions extend TTL-like mechanisms and rely on two knobs to tune the time between insertions and evictions given a target hit rate. We show the general benefits of hysteresis and the particular improvement of the two thresholds strategy in reducing download times, making the system more predictable and accounting for different costs associated with object retrieval.
... However, spanning trees are costly to maintain on large networks with heavy churn. The network traffic can be significantly reduced using adapted replication strategies and random walks [18]. Flooding can also be limited by using multiple overlays as in Semantic Overlay Network (SON) or routing indices [5,7]. ...
This article investigates the application to enhance event correlation and automation within IBM Netcool environments. Drawing on real-world implementations, and it explores practical strategies for improving service management through advanced analytics, automation, and integration. The study focuses on leveraging Netcool Operations Insight (NOI), Netcool Omnibus, and related components to build robust managed services platforms. It details the development of custom Impact policies, the utilization of Cognos for advanced event analytics, and the automation of incident response through Perl and shell scripting. The findings demonstrate the significant benefits of an open shift driven approach in streamlining operations, reducing incident resolution times, and improving overall service reliability.
Information systems (IS) are composed of distinct, interrelated elements that aim to fulfill desired features. This chapter introduces the concept of IS architecture as a way to meaningfully describe and design the underlying structure of an IS. It presents nine basic principles of IS architectures and explains them using the ex-ample of the cloud-based storage service Dropbox. This introduction to IS archi-tecture also introduces the most common architectural patterns (i.e. client-server architecture, tier architectures, peer-to-peer architecture, model view controller, and service-oriented architecture) in the realm of Internet computing and briefly discusses their main strengths and weaknesses.
We investigate quantum walks which play an important role in the modelling of many phenomena. The detailed and thorough description is given to the discrete quantum walks on a line, where the total quantum state consists of quantum states of the walker and the coin. In addition to the standard walker probability distribution, we introduce the coin probability distribution which gives more complete quantum walk description and novel visualization in terms of the so called polyanders (analogs of trianders in DNA visualization). The methods of final states computation and the Fourier transform are presented for the Hadamard quantum walk.
_____Appeared: in book "Innovative Quantum Computing" IOP Publishing (Bristol, 2023) by S. Duplij, R. Vogl (as Chapter 6), ISBN: 9780750352796, https://store.ioppublishing.org/page/detail/Innovative-Quantum-Computing/?K=9780750352796, https://doi.org/10.1088/978-0-7503-5281-9, DOI: 10.1088/978-0-7503-5281-9, https://arxiv.org/abs/2311.00409
Each and every end-to-end systems try to mask the information and details of their users for privacy considerations. Existing quality of being anonymous approaches are mainly path-based: peers have to pre-construct an anonymous path before transmissio of any files and queries.The overhead of maintaining and updating such paths is significantly high also introduce high cost. Its called as blindly assigned path. We propose Rumor Riding (RR), a lightweight and non-path-based mutual anonymity protocol for decentralized P2P systems. Employing a random walk mechanism, RR takes advantage of lower overhead by mainly using the symmetric cryptographic algorithm. Accelerating the query speed. Introducing mimic traffic to confuse attackers. Mimic traffic generates duplicate cipher and key rumor to confuse the attackers. This mimic traffic generates traffic in a purposefully irregular manner. Mimic is undetectable by any known detection technique at without loss of throughput.
In this chapter we elaborate on two decisive aspects for the development of Swarm computing. First, an initial set of Security requirements is detailed. Addressing these requirements is considered of upmost importance for the development of Swarm computing beyond the preliminary experimentation presented in this book. Moreover, this chapter points out the core role that existing developments in distributed systems theory implemented in P2P works occupy in this work. It specifically highlights how concepts of distributed nodes coordination services and consensus algorithms supports the implantation of overlay networks in Swarm computing and Ad-hoc Edge Cloud Architectures.
In content sharing with Peer-to-Peer (P2P) network systems, content has been smoothly acquired and prevented from being lost by replication of the content and deploying replicas on multiple peers. However, in some conventional methods, it takes a long time for the replicas of content to be spread over the network, which makes stable content sharing difficult. In this paper, we propose a method to predict the change in popularity of each content item over time and to deploy an appropriate number of replicas of popular content evenly on the network before the supply becomes insufficient. The method also keeps the ratio of each content replica's total stored capacity to the whole storage capacity in P2P in proportion to its demand, while considering each replica's size of capacity. Furthermore, we confirm the effectiveness of the proposed method by computer simulations.
The proliferation of Internet of Things (IoT) data and innovative mobile services has promoted an increasing need for low-latency access to resources such as data and computing services. Mobile edge computing has become an effective computing paradigm to meet the requirement for low-latency access by placing resources and dispatching tasks at the edge clouds near mobile users. The key challenge of such solution is how to efficiently place resources and dispatch tasks in the edge clouds to meet the QoS of mobile users or maximize the platform's utility. In this paper, we study the joint optimization problem of resource placement and task dispatching in mobile edge clouds across multiple timescales under the dynamic status of edge servers. We first propose a two-stage iterative algorithm to solve the joint optimization problem in different timescales, which can handle the varieties among the dynamic of edge resources and/or tasks. We then propose a reinforcement learning (RL) based algorithm which leverages the learning capability of Deep Deterministic Policy Gradient (DDPG) technique to tackle the network variation and dynamic as well. The results from our trace-driven simulations demonstrate that both proposed approaches can effectively place resources and dispatching tasks across two timescales to maximize the total utility of all scheduled tasks.
Data centre networks (DCN) is emerging as one of the striving research areas in the data communication and networking domain. The information access across DCN involves various issues due to the unexpected disconnection of networks. This means that the nodes access can be improved when the information presence on neighbouring nodes is aligned accordingly. This paper deals with a novel replication protocol by using an information presence algorithm and a cooperative caching to enhance the data availability across various nodes. The implementation shows that the proposed algorithm outperforms the existing data management algorithms available in DCN.
In recent years, edge computing has become an increasingly popular computing paradigm to enable real-time data processing and mobile intelligence. Edge computing allows computing at the edge of the network, where data is generated and distributed at the nearby edge servers to reduce the data access latency and improve data processing efficiency. One of the key challenges in data-intensive edge computing is how to place the data at the edge clouds effectively such that the access latency to the data is minimized. In this paper, we study such a data placement problem in edge computing while different data items have diverse popularity. We propose a popularity based placement method which maps both data items and edge servers to a virtual plane and places or retrieves data based on its virtual coordinate in the plane. We then further propose additional placement strategies to handle load balancing among edge servers via either offloading or data duplication. Simulation results show that our proposed strategies efficiently reduce the average path length of data access and the load-balancing strategies indeed provide an effective relief of storage pressures at certain overloaded servers.
We consider the problem of timely exchange of updates between a central station and a set of ground terminals
V
, via a mobile agent that traverses across the ground terminals along a mobility graph
. We design the trajectory of the mobile agent to minimize average-peak and average age of information (AoI), two recently proposed metrics for measuring timeliness of information. We consider randomized trajectories, in which the mobile agent travels from terminal
i
to terminal
j
with probability
. For the information gathering problem, we show that a randomized trajectory is average-peak age optimal and factor-
average age optimal, where
is the mixing time of the randomized trajectory on the mobility graph
G
. We also show that the average age minimization problem is NP-hard. For the information dissemination problem, we prove that the same randomized trajectory is factor-
average-peak and average age optimal. Moreover, we propose an age-based trajectory, which utilizes information about current age at terminals, and show that it is factor-2 average age optimal in a symmetric setting.
We propose a decentralized caching policy for wireless heterogeneous networks that makes content placement decisions based on pairwise interactions between cache nodes. We call our proposed scheme
-exclusion cache placement
(
), where a parameter
controls an exclusion radius that discourages nearby caches from storing redundant content.
takes into account item popularity and the nodes’ caching priorities and leverages negative dependence to relax the classic 0–1 knapsack problem to yield spatially balanced sampling across caches. We show that
guarantees a better concentration (reduced variance) of the required cache storage size than the state of the art, and that the cache size constraints can be satisfied with high probability. Given a cache hit probability target, we compare the 95% confidence intervals of the required cache sizes for three caching schemes: (i) independent placement, (ii) hard exclusion caching (
), and (iii) the proposed
approach. For uniform spatial traffic, we demonstrate that
provides approximately a 3x and 2x reduction in required cache size over (i) and (ii), respectively. For non-uniform spatial traffic based on realistic peak-hour variations in urban scenarios, the gains are even greater.
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