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Recently, the demand for scientific computing on HPC systems has grown in popularity. However, the runtime environment is a standpoint when there are many kinds of different applications with different requirements. Moreover, an HPC... more
Recently, the demand for scientific computing on HPC systems has grown in popularity. However, the runtime environment is a standpoint when there are many kinds of different applications with different requirements. Moreover, an HPC system cannot satisfy all of these requirements of environment. This becomes more and more considerable in the case of applications running on heterogeneous systems (e.g., CPU/Intel Xeon Phi based cluster). Generally, two main problems needing to be tackled in HPC systems are runtime environment and workload management. In terms of lightweight virtualization, Docker facilitates the isolation of different applications as well as runtime environments on the same host operating system. In addition, with huge advantages, batch job scheduler plays a vital role in management and operation. In this paper, we adopt an approach by combining containerization and HPC workload management to support the submission of a variety of applications. Practically, we perform the experiments on a heterogeneous cluster with CPU and Intel Xeon Phi coprocessor. The results show that there is a slightly different about the performance of jobs which are submitted by the normal way and containerized way. However, the experimental result highlights that the cost of containerizing HPC applications is negligible, and this can be applied in practice to fulfill user's requirement.
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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... more
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 leverage resource and contract heterogeneity to optimize cloud costs. In this paper, we propose a novel opportunistic resource scaling approach that exploits both resource and contract heterogeneity to achieve cost-effective resource allocations. We model resource allocation as an unbounded knapsack problem, and resource scaling as an one-step ahead resource allocation problem. Based on these models, we propose two scaling strategies: (a) delta capacity optimization, which focuses on optimizing costs for the difference between existing resource allocation and the required capacity based on the forecast workload, and (b) full capacity optimization, which focuses on optimizing costs for resource capacity corresponding to the forecast workload. We evaluate both strategies using two real world workload datasets, and compare them against three different scaling strategies. The results show that our proposed approach, particularly full capacity optimization, outperforms all of them and offers in excess of 70% cost savings compared to the traditional scaling approach.
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Antifragile systems enhance their capabilities and become stronger when exposed to adverse conditions, stresses or attacks, making antifragility a desirable property for cyber defence systems that operate in contested military... more
Antifragile systems enhance their capabilities and become stronger when exposed to adverse conditions, stresses or attacks, making antifragility a desirable property for cyber defence systems that operate in contested military environments. Self-improvement in autonomic systems refers to the improvement of their self-* capabilities, so that they are able to (a) better handle previously known (anticipated) situations, and (b) deal with previously unknown (unanticipated) situations. In this position paper, we present a vision of using self-improvement through learning to achieve antifragility in autonomic cyber defence systems. We first enumerate some of the major challenges associated with realizing distributed self-improvement. We then propose a reference model for middleware frameworks for self-improving autonomic systems and a set of desirable features of such frameworks.
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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... more
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 of researchers in the field has been paid to the traditional and basic problems in reasoning about actions such as the frame, the qualification and the ramification problems, approaches to these problems within our formalisation lie at heart of the expositions presented in this paper.
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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... more
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 paper proposes a generic multi-hop probabilistic forwarding scheme that achieves these requirements for event-driven safety messages, is compatible with the 802.11 broadcasting protocol and inherits some of the best features of solutions proposed so far for vehicular safety applications. In addition, we develop a unified and comprehensive analytical model to evaluate the performance of the proposed scheme taking into account the effect of hidden terminals, vehicle densities, and the spatial distribution of the multiple forwarders, in a one-dimensional highway scenario. Our numerical experiments confirm the accuracy of the model and demonstrate that the proposed protocol can improve the packet delivery performance by up to 209 percent, while maintaining the delay well below the required threshold. Finally, the utility of the analytical model is demonstrated via an optimal design for the coefficients of a forwarding probability function in the proposed scheme.
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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... more
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 ...
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ABSTRACT 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... more
ABSTRACT 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 protocols which define their communicative behaviour and are guided by private decision-making strategies which define their strategic behaviour. Time plays a crucial role in decision-making, necessitating support for modelling temporal constraints in interaction protocol specifications. In this paper, we propose two temporal constraints, namely the deadline constraint and the validity constraint and use the Amazon EC2 Spot Bid Request lifecycle to illustrate the need for supporting them. We extend our previous state based model for SLA interaction protocols [4] to support timesensitive conversations. We have implemented our proposed approach in AutoSLAM [3], a policy-driven framework for automated SLA establishment, and validated it through a realworld usecase scenario of procuring computing resources from Amazon Elastic Compute Cloud (EC2).
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In multi-issue negotiations, autonomous agents can act co- operatively to benefit from mutually preferred agreements. However, empirical evidence suggests that they often fail to search for joint gains and end up with inefficient results.... more
In multi-issue negotiations, autonomous agents can act co- operatively to benefit from mutually preferred agreements. However, empirical evidence suggests that they often fail to search for joint gains and end up with inefficient results. To address this problem, this paper proposes a novel mediated negotiation procedure to support the negotiation agents in reaching an efficient and fair agreement in bilateral
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ABSTRACT 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... more
ABSTRACT 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 Cloud Marketplace (SCM) as a platform for trading cloud services based on intelligent agent technology. Software agents represent the cloud service consumers and providers in the marketplace, and make intelligent decisions on their behalf. The platform enables participants to use different trading policies in order to automate and improve the efficiency of resource trading. Moreover, SCM supports multimarket trading, where different market mechanisms can be deployed. We have used the SCM platform to test different market mechanisms developed within our research group. Our experimental evaluation demonstrates that Smart Cloud Marketplace is a useful, flexible and effective platform for conducting experiments and ultimately for trading cloud services.
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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... more
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 distribution of resulting gains from trade to prevent bargainers from misrepresenting their valuations of the negotiation outcomes. Our mechanism is based on rewarding concession-making agents with larger shares of the obtainable surplus. We show that the likelihood for the negotiators to reach agreement is accordingly increased and the negotiation efficiency is improved.
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ABSTRACT 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... more
ABSTRACT 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 the multi-agent systems. In this paper, we present a merging approach based on the negotiation techniques. A new model is proposed in which agents gradually build their common belief base from the beliefs that they provide in each round of negotiation. A set of postulates is also introduced to characterize the logical properties of the merging results.
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Abstract. Dialogs in formal domains, such as mathematics, are characterized by a mixture of telegraphic natural language text and embedded formal expressions. Due to the lack of empirical data for such environments, we have collected a... more
Abstract. Dialogs in formal domains, such as mathematics, are characterized by a mixture of telegraphic natural language text and embedded formal expressions. Due to the lack of empirical data for such environments, we have collected a corpus of dialogs with a simulated tutoring system for teaching proofs in naive set theory. The analysis of this corpus enabled us to identify genre-specific variants of linguistic phenomena which impose specific requirements on natural language dialog management.
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... about actions. CITED BY, Quoc Bao Vo , Norman Y. Foo , Joe Thurbon, Semantics for a theory of defeasible reasoning, Annals of Mathematics and Artificial Intelligence, v.44 n.1-2, p.87-119, May 2005. INDEX TERMS Primary ...
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Our work addresses assertion retrieval and application in theorem proving systems or proof planning systems for classical first-order logic. We propose a distributed mediator M between a mathemat-ical knowledge base KB and a theorem... more
Our work addresses assertion retrieval and application in theorem proving systems or proof planning systems for classical first-order logic. We propose a distributed mediator M between a mathemat-ical knowledge base KB and a theorem proving system TP which is ...
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In this paper we report on a Wizard-of-Oz (WOz) experiment which was conducted in order to collect written empirical data on mathematics tutorial dialogues in German. We present a methodological approach for optimising the gains from WOz... more
In this paper we report on a Wizard-of-Oz (WOz) experiment which was conducted in order to collect written empirical data on mathematics tutorial dialogues in German. We present a methodological approach for optimising the gains from WOz empirical studies. We show the results ...