Bao Quoc Vo

Swinburne University of Technology · Faculty of Information and Communication Technologies

BACKGROUND Machine reading comprehension (MRC) tasks have been developed, with state-of-the-art extractive methods having achieved comparable or better accuracy than human performance on benchmark datasets. However, such models are not as successful when adapted to complex domains such as healthcare. One of the main reasons is that the context that...

Background Extractive methods for machine reading comprehension (MRC) tasks have achieved comparable or better accuracy than human performance on benchmark data sets. However, such models are not as successful when adapted to complex domains such as health care. One of the main reasons is that the context that the MRC model needs to process when op...

A resilient system can survive attacks and failures by autonomously adapting and managing its own functionality. An antifragile system is not only resilient but is also able to enhance its capabilities and become more resilient as a result of endogenous and exogenous stressors. This makes antifragility a highly desirable property of cyber defense s...

BACKGROUND Question answering (QA) and machine reading comprehension (MRC) tasks have been developed, with state-of-the-art extractive methods having achieved comparable or better accuracy than human performance on benchmark datasets. However, such models are not as successful when adapted to complex domains such as healthcare. One of the main reas...

Low-cost transient resources such as Amazon's Elastic Compute Cloud (EC2) Spot instances can be opportunistically leveraged to reduce the ongoing costs of cloud applications. However, they are susceptible to unilateral revocations by the vendor making them a risky proposition for long-running applications with strict performance requirements. It is...

This paper studies a heterogeneous task allocation problem with the budget constraint. Existing works on task allocation mainly tackle this well-known NP-hard problem from an optimisation perspective. They have not been able to cater to the extra needs of scalability and robustness in large-scale systems. Furthermore, some general allocation mechan...

Ensuring cost-effective end-to-end QoS in an IoT data processing pipeline (DPP) is a non-trivial task. A key factor that affects the overall performance is the amount of computing resources allocated to each service in the pipeline. In this demo paper, we present AuraEN, an Autonomous resource allocation ENgine that can proactively scale the resour...

Agent-based evolutionary game theory studies the dynamics of the autonomous agents. It is important for application that relies on the agents to perform the automated tasks. Since the agents make their own decision, therefore the stability of the interaction needs to be comprehended. The current state of the art in agent-based replicator dynamics a...

Cloud consumers have access to an increasingly diverse range of resource and contract options, but lack appropriate resource scaling solutions that can exploit this to minimize the cost of their cloud-hosted applications. Traditional approaches tend to use homogeneous resources and horizontal scaling to handle workload fluctuations and do not lever...

Medical data streams processing becomes increasingly important since it extracts critical information from a continuous flow of patient data. Various types of problems have been studied on medical data streams, such as classification, clustering, anomaly detection, etc.; however, efficient evaluation of cumulative frequency queries has not been wel...

In a bid to minimize idle capital and maximize resource utilization and revenue, cloud infrastructure providers are increasingly offering customers a multitude of customized and flexible resource configurations and purchasing options. Yet, market research identifies cost optimization and performance optimization as the two main challenges for cloud...

Previously, Amazon EC2 Spot prices were always driven by short-term trends in supply and demand, requiring consumers to have an in-depth understanding of Spot markets and the bidding process in order to make “intelligent” time-vs-money-vs-value trade-offs. However, with the newly announced streamlined access model for Spot instances, Amazon states...

Ensuring cost-effective end-to-end QoS in a multilayer, multi-service, IoT data processing pipeline is a non-trivial challenge. The uncertainties surrounding the 3Vs of streaming data – variety, velocity and volume – impose dynamic QoS driven resource requirements on each component (or service) of the pipeline and make adaptive resource management...

Semi-Structured data has been extensively adopted in numerous web applications as a standard data exchange format. XML is one of the most popular formats on the web due to its wide usage in representing and transferring data. Most real-world applications require low latency for transferring a large amount of web data between clients and the applica...

Web data clustering has been widely studied in the data mining communities. However, dynamic maintenance of the web data clusters is still a challenging task. In this paper, we propose a novel framework called XClusterMaint which serves for both clustering and maintenance of the XML documents. For clustering, we take both structure and content into...

Vehicle-to-vehicle (V2V) communication enables exchanging information between vehicles by broadcasting safety and beacon messages. Safety applications based on a so-called dedicated short-range communication (DSRC), which are one of the main applications of V2V, require a very strict network performance for safety messages. In this paper, we invest...

In this paper, we study forecasting through time series decomposition to predict Amazon Elastic Compute Cloud (EC2) Spot prices. To achieve this, we first decompose the Spot price history into time series components; each component, which can exhibit deterministic or non-deterministic qualities, is then separately forecast using different standard...

Optimum Bid price estimation is crucial for Amazon Elastic Compute Cloud (EC2) consumers if they want to secure uninterrupted access to Spot instances at reduced costs. We recently reported that Bid price estimation is an implicit function of seasonal components and extreme spikes in the Spot price history. In this paper we apply time series foreca...

Consumers can realize significant cost savings by procuring resources from computational spot markets such as Amazon Elastic Compute Cloud (EC2) Spot Instances. They can take advantage of the price differentials across time slots, regions, and instance types to minimize the total cost of running their applications on the cloud. However, Spot market...

We aim to understand the fundamental design correspondences between TPC-W and RUBiS, two benchmark applications modeled after the well-known E-commerce solutions Amazon and eBay, respectively. Furthermore, we investigate how these benchmarks reflect the design principles of real-world applications by comparing them against Qualitas Corpus, offering...

Classic results in game theory state that private information is a cause for a negotiation to end with suboptimal outcome. Subse- quently, private information is a compelling explanation for the frequent occurrence of negotiation breakdowns or costly delays. In this paper, we propose a mechanism for improving efficiency of negotiation outcome for m...

Modern cloud service-based applications (CSBAs) are increasingly being composed from multiple components that require and consume services at different layers of the cloud stack. The diverse, dynamic and unpredictable nature of both the cloud services and the application workloads makes quality-assured provision of CSBAs a major challenge. Elastici...

The increasingly growing supply and demand for infrastructure as a service (IaaS) makes cloud trading possible in an open exchange (OCX) marketplace. The mechanisms based on economic principles show promise in addressing the problem of efficient cloud resource provisioning in such a marketplace, including resources allocation and pricing. Therefore...

Safety applications based on the dedicated short-range communication (DSRC) in vehicular networks have very strict performance requirements for safety messages (in terms of delay and packet delivery). However, there is a lack of systematic approach to achieve the performance requirements by leveraging the potential of multi-hop forwarding. This pap...

This paper explores the application of inequality indices, a concept successfully applied in comparative software analysis among many application domains, to find the optimal value k for k-means when clustering road traffic data. We demonstrate that traditional methods for identifying the optimal value for k (such as gap statistic and Pham et al.'s...

Service Level Agreement (SLA) establishment can be viewed as a complex business process in which consumers and providers, with varying and potentially conflicting preferences, interact with one another in order to reach mutually acceptable agreements over the service usage terms and conditions. These interactions are governed by public interaction...

The increasingly growing supply and demand of infrastructure as a service (IaaS) makes cloud trading possible and desirable in open cloud exchange marketplaces. The automation of cloud services trading in such marketplaces is an essential next step in the cloud market evolution, and it requires a proper market mechanism to effectively and efficient...

Cloud migration allows organizations to benefit from reduced operational costs, improved flexibility, and greater scalability, and enables them to focus on core business goals. However, it also has the flip side of reduced visibility. Enterprises considering migration of their IT systems to the cloud only have a black box view of the offered infras...

Belief merging is an active research field with many important applications. Most existing work addresses the belief merging issue using a centralised approach. In this paper, we investigate a distributed approach to the problem of belief merging. The contribution of this paper is two-fold: (i) we develop a negotiation-based model for belief mergin...

Migration to the cloud offers several benefits including reduced operational costs, flexibility, scalability, and a greater focus on business goals, but it also has a flip side reduced visibility. Organizations only have a blackbox view of cloud servers and while pricing and specification information is publicly available, there is limited informat...

Service Level Agreement (SLA) establishment can be viewed as a cross-organizational business process, in which consumers and providers, with varying and potentially conflicting requirements and capabilities, interact with one another in order to try and reach common agreements over the service usage terms and conditions. These interactions are gove...

In this paper, we study the problem of collective decision-making over combinatorial domains, where the set of possible alternatives is a Cartesian product of (finite) domain values for each of a given set of variables, and these variables are not preferentially independent. Due to the large alternative space, most common rules for social choice ca...

In recent years there has been an exponential growth in the number of vendors offering Infrastructure-as-a-Service (IaaS), with a corresponding increase in the number of enterprises looking to migrate some, or all of their IT systems to the cloud. Prospective cloud consumers need to identify providers that offer resources with the most appropriate...

In vehicle-to-vehicle communication, safety messages could be broadcasted over one-hop or multi-hop using different transmission ranges to warn each other of changing conditions or dangers ahead. We investigate the broadcast performance considering one-hop and multi-hop transmissions and study the effect of different transmission ranges on the mult...

Cloud computing services are rapidly gaining popularity with more and more businesses actively migrating to the cloud, and many new cloud providers emerging. In such circumstances, there is a need for a market platform that allows for automated trading of cloud services between numerous independent users. Therefore, in this paper we propose Smart C...

In multi-issue negotiations, autonomous agents can act cooperatively to benefit from mutually preferred agreements. However, empirical evidence suggests that autonomous agents often fail to elicit possible joint gains and end up with inefficient results in multi-issue negotiation, especially when it involves multiple parties. In order to address th...

Cloud resource allocation and pricing is a significant and challenging problem for modern cloud providers, which needs to be addressed. In this work, we propose an adaptive greedy mechanism, which is a new type of greedy market mechanism for efficient cloud resource allocation. The mechanism is combinatorial and it is designed to be operated by a s...

With the rapidly growing demand for the cloud services, a need for efficient methods to trade computing resources increases. Commonly used fixed-price model is not always the best approach for trading cloud resources, because of its inflexible and static nature. Market-based trading shows promise for more efficient resource allocation and pricing i...

Detecting inconsistencies is a critical part of requirements engineering (RE) and has been a topic of interest for several decades. Domain knowledge and semantics of requirements not only play important roles in elaborating requirements but are also a crucial way to detect conflicts among them. In this paper, we present a novel knowledge-based RE f...

We develop a framework for preference aggregation in multi-attribute, multi-valued domains, where agents’ preferences are represented by Conditional Preference Networks (CP-nets). Most existing work either does not consider computational requirements, or depends on the strong assumption that the agents can express their preferences by acyclic CP-ne...

With the rapidly growing demand for the cloud services, a need for efficient methods to trade computing resources increases. Commonly used fixed-price model is not always the best approach for trading cloud resources, because of its inflexible and static nature. Dynamic trading systems, which make use of market mechanisms, show promise for more eff...

This paper investigates the maximum achievable channel throughput in a single‐channel and single‐hop wireless sensor network using IEEE 802.15.4 Medium Access Control (MAC) protocol. We introduce a simple mean‐field approach to model the Carrier Sense Multiple Access with Collision Avoidance mechanism of the 802.15.4 MAC protocol under unsaturated...

This paper develops a simple, robust framework for the problem of finding the route with the least expected travel time from any node to any given destination in a stochastic and time-dependent network. Spatial and temporal link travel time correlations are both considered in the proposed solution, which is based on a dynamic programming approach....

Classic results in bargaining theory state that private information necessarily prevents the bargainers from reaping all possible gains from trade. In this paper we propose a mechanism for improving efficiency of negotiation outcome for multilateral negotiations with incomplete information. This objective is achieved by introducing biased distribut...

Cloud computing offers a realization of SOA in which IT resources are dynamically provisioned as services to consumers using flexible provisioning and pricing models. When provisioning such services, providers and consumers must first agree over the service usage terms and conditions, which are captured in Service Level Agreements (SLAs). In this p...

As the rate of cloud computing adoption grows, so does the need for consumption assistance. Enterprises looking to migrate their IT systems to the cloud require assistance in identifying providers that offer resources with the most appropriate pricing and performance levels to match their specific business needs. In this paper, we present Smart Clo...

Automated negotiation is one of the most common approaches used to make decisions and manage disputes between computational entities leading them to optimal agreements. Many existing works tackle single-issue negotiations and the negotiation environment is assumed to be static so that the agents can make decisions based solely on the proposals of t...

As the rate of cloud computing adoption grows, so does the need for consumption assistance. Enterprises that are looking to migrate their IT systems to the cloud, would like to quickly identify providers that offer resources with the most appropriate pricing and performance levels to match their specific business needs. However, no two vendors offe...

Advancements in the efficiency, quality and manufacturability of sensing and communication systems are driving the field of intelligent transport systems (ITS) into the twenty first century. One key aspect of ITS is the need for efficient and robust integrated network management of urban traffic networks. This paper presents a general model predict...

In this paper, we study the problem of collective decision-making over combinatorial domains. We focus on a particular social choice rule, namely Smith/Minimax. We introduce a distributed protocol for collective decision-making, which is general enough and does not restrict the choice of preference representation languages. The final decision chose...

Flexible and adaptive quality-of-service (QoS) is desirable for distributed real-time applications, such as e-commerce, or multimedia applications. The objective of this research is to dynamically instantiate composite services by effectively utilising the collective capabilities of the resources to deliver distributed applications. Related to this...

In game theory, the notion of expectation is made implicit. That is, most game-theoretic solution concepts, such as equilibrium, rationalizability, assume that agents expect one another to play their respective strategies according to the solution(s) induced by these solution concepts. This assumption limits the applicability of these solution conc...

This paper presents an axiomatic model for merging stratified belief bases by negotiation. We introduce the concept of mapping solution, which maps the preferences of agents into layers, as a vehicle to represent the belief states of agents and their attitudes towards the negotiation situations. The belief merging process in our model is divided in...

Requirements engineering (RE) is a coordinated effort to allow clients, users, and software engineers to jointly formulate assumptions, constraints, and goals about a software solution. However, one of the most challenging aspects of RE is the detection of inconsistencies between requirements. To address this issue, we have developed REInDetector,...

Optimal route selection with reliable expected travel time has been a focus of research in transportation networks where the reliability is subject to many uncertainty factors such as traffic incidents or recurring traffic congestions. In this paper we develop an approximation method to obtain the reliability of a route travel time in a stochastic...

Belief merging has been an active research field with many important applications. The major approaches for the belief merging problems, considered as arbitration processes, are based on the construction of the total pre-orders of alternatives using distance functions and aggregation functions. However, these approaches require that all belief base...

Cloud Computing is the latest paradigm proposed toward fulfilling the vision of computing being delivered as an utility such as phone, electricity, gas and water services. It enables users to have access to computing infrastructure, platform and software as services over the Internet. The services can be accessed on demand and from anywhere in the...

The end-to-end QoS negotiation for service level agreement establishment for composite services involves compound multi-party negotiations in which the composite service provider concurrently negotiates with multiple candidates for each atomic service, selecting the one that best satisfies the atomic service QoS preferences while ensuring that the...

In this paper, we introduce axiomatic and strategic models for bargaining and investigate the link between the two. Bargaining situations are described in propositional logic while the agents' preferences over the outcomes are expressed as ordinal preferences. Our main contribution is an axiomatic theory of bargaining. We propose a bargaining solut...

AutoSLAM (Automated SLA Management) is a policy-based framework for the automated establishment of Service Level Agreements (SLAs) in open, diverse and dynamic Service Oriented Architecture (SOA) environments. The novelty of our framework lies in the support for multiple SLA interaction models, giving service consumers and providers the flexibility...

We propose a policy-based framework for the automated establishment of SLAs for cloud computing services. The proposed framework supports multiple interaction models for SLA establishment giving consumers and providers the flexibility to choose one that is most appropriate in a given context, while simultaneously supporting multiple concurrent SLA...

We study the problem of agent-based negotiation in combinatorial domains. It is difficult to reach optimal agreements in bilateral or multi-lateral negotiations when the agents' preferences for the possible alternatives are not common knowledge. Self-interested agents often end up negotiating inefficient agreements in such situations. In this paper...

Detecting inconsistencies is a critical part of requirements engineering (RE) and has been a topic of interest for several decades. Domain knowledge and semantics of requirements not only play important roles in elaborating requirements but are also a crucial way to detect conflicts among them. In this paper, we present a novel knowledge-based RE f...

This paper studies the problem of computing aggregation rules in combinatorial domains, where the set of possible alternatives is a Cartesian product of (finite) domain values for each of a given set of variables, and these variables are usually not preferentially independent. We propose a very general heuristic framework SC* for computing differen...

In this paper we present the cloud broker which can help decision makers assess the feasibility of adopting cloud computing in their organizations. It matches their requirements in terms of infrastructure, costs, geographic location and other requisite criteria, to the capabilities of the cloud service providers. Additionally, it allows them to tes...

Route finding issues have always been a significant research focus in intelligence transportation system. Many solution models have been proposed in the previous work and analyzed in detail. Successive link travel time correlation has been identified to play an important role in these models to realistically reflect the property of traffic flows. I...

Belief merging has been an active research field with many important applications. Many approaches for belief merging have been proposed, but these approaches only take the belief bases as inputs without the adequate attention to the role of agents, who provide the belief bases, thus the results achieved are merely ideal and difficult to apply in t...

We present a uniform non-monotonic solution to the problems of reasoning about action on the basis of an argumentation-theoretic approach. Our theory is provably correct relative to a sensible minimisation policy introduced on top of a temporal propositional logic. Sophisticated problem domains can be formalised in our framework. As much attention...

We propose a policy-based framework for the QoS differentiated provisioning of services. The proposed frame-work improves the state-of-the-art in policy-based preference specification by combining cardinal and ordinal preferences. We describe the underlying models, focussing on the key features and contributions of the proposed framework. We also s...

This paper studies the problem of collective decision-making in combinatorial domain where the agents' preferences are represented by qualitative models with TCP-nets (Tradeoffs-enhanced Conditional Preference Network). The features of TCP-nets enable us to easily encode human preferences and the relative importance between the decision variables;...

CP-net (Conditional Preference Network) is one of the extensively studied languages for representing and reasoning with preferences. The fundamental operation of dominance testing in CP-nets, i.e. determining whether an outcome is preferred to another, is very important in many real-world applications. Current techniques for solving general dominan...

Communication is a key capability of autonomous agents in a multi-agent system to exchange information about their environment. It requires a naming convention that typically involves a set of predefined names for all objects in the environment, which the agents share and understand. However, when the agents are heterogeneous, highly distributed, a...

This paper studies the problem of majority-rule-based collective decision-making where the agents' preferences are represented by CP-nets (Conditional Preference Networks). As there are exponentially many alternatives, it is impractical to reason about the individual full rankings over the alternative space and apply majority rule directly. Most ex...

In classical decision theory, the agents’ preferences are typically modelled with utility functions that form the base for individual and multi-agent decision-making. However, utility-based preference elicitation is often complicated and sometimes not so user-friendly. In this paper, we investigate the theory of CP-nets (conditional preference netw...

This paper addresses a coordination problem during concurrent multiple bilateral negotiations. Real time decisions need to be taken during negotiation to ensure that the overall negotiation process is successful in terms of achieving a valuable agreement (an agreement with high utility). Existing approaches for managing concurrent multiple bilatera...

The end-to-end QoS negotiation for SLA establishment for composite services involves compound multi-party negotiations in which the composite service provider concurrently negotiates with multiple candidates for each atomic service, selecting the ones that best satisfy the atomic service QoS preferences while ensuring that end-to-end QoS requiremen...

We present a policy-centered QoS meta-model which can be used by service providers and consumers alike to express capabilities, requirements, constraints, and general management characteristics relevant for SLA establishment in service aggregations. We also provide a QoS assertion model which is generic, domain-independent and conforming to the WS-...

This paper studies the problem of collective decision-making in the case where the agents' preferences are represented by CP-nets (conditional preference networks). In many real-world decision-making problems, the number of possible outcomes is exponential in the number of domain variables. Most related works either do not consider computational co...

This paper addresses the problem of collective decision making in the case where the agents' preferences are represented by CP-nets (Conditional Preference Networks). Most existing works either do not consider the computational issues, or depend on a strong assumption that all the agents share a common preferential independence structure. To this e...