Showing papers in "Multiagent and Grid Systems in 2014"

Auction based resource allocation in cloud computing

Abstract: Resource allocation is fundamental function of cloud computing. Different auction models offer a variety of market driven resource allocation mechanisms. This paper studies auction based resource allocation for cloud computing. First, a framework of auction based resource allocation is presented for cloud computing, and the main issues are also discussed in the design of auction based resource allocation mechanisms. Then, an overview is presented upon the state-of-the-art of auction based resource allocation in cloud computing.

Reputation-based multi-dimensional trust model in cloud manufacturing service platform

Abstract: In previous researches of cloud manufacturing services, trust evaluation models were not flexible enough and subjective preferences of agents were not reflected either. For this issue, a five-dimensional trust evaluation system is built, and a reputation-based trust evaluation algorithm (RBTE) is also proposed. The direct trust rank (DT), friend reputation (RF) and platform reputation (RP) of the agent could be integrated into the trust rank (TR) with the weight vector through this algorithm. Combined with similarities of trust evaluation process, a trust network building approach is put forward in this research. The trust rank update algorithm also achieved dynamic rewards or punishments over time. Experimental results has shown good executing efficiency, and reflected the subjective preference of the transaction agent to a certain extent.

A dynamic replication strategy based on categorization for Data Grid

Abstract: Data Replication is copying the data from a certain location to another location. Replication is used in Data Grid to have two or more copies of the same data at different locations. In this paper, a Category-based dynamic replication strategy (CDRS) is proposed. The strategy takes into account that the replicas exist on a node belong to different categories. Each of these categories is given a value that determines its importance for the node. When the node's storage is full, the node starts to store only the replicas that belong to the category with the highest value. The results of the simulations show that the new proposed strategy achieved better performance than Plain Caching and Fast Spread strategies in terms of total transit time and total bandwidth consumption.

An electricity market with fast bidding, planning and balancing in smart grids

Abstract: In future energy systems, peaks in the daily electricity generation and consumption are expected to increase. The "smart grid" concept aims to maintain high levels of efficiency in the energy system by establishing distributed intelligence. Software agents (operating on devices with unknown computational capabilities) can implement dynamic and autonomous decision making about energy usage and generation, e.g. in domestic households, farms or offices. To reach satisfactory levels of efficiency and reliability, it is crucial to include planning-ahead of the energy-involving activities. Market mechanisms are a promising approach for large-scale coordination problems about energy supply and demand, but existing electricity markets either do not involve planning-ahead sufficiently or require a high level of sophistication and computing power from participants, which is not suitable for smart grid settings. This paper proposes a new market mechanism for smart grids, ABEM (Ahead-and Balancing Energy Market). ABEM performs an ahead market and a last-minute balancing market, where planning-ahead in the ahead market supports both binding ahead-commitments and reserve capacities in bids (which can be submitted as price functions). These features of planning-ahead reflect the features in modern wholesale electricity markets. However, constructing bids in ABEM is straightforward and fast. We also provide a model of a market with the features mentioned above, which a strategic agent can use to construct a bid (e.g. in ABEM), using a decision-theoretic approach. We evaluate ABEM experimentally in various stochastic scenarios and show favourable outcomes in comparison with a benchmark mechanism.

Utilizing costly coordination in multi-agent joint exploration

Abstract: This paper studies distributed cooperative multi-agent exploration methods in settings where the exploration is costly and the overall performance measure is determined by the minimum performance achieved by any of the individual agents. Such an exploration setting can commonly be found in multi-agent systems, e.g., in multi-channel cooperative sensing where the quality of the overall connection is constrained by the individual qualities of the connections used by the different agents. The goal in such problems is to optimize the process as a whole, considering the tradeoffs between the quality of the solution obtained and the cost associated with the exploration and coordination between the agents. The methods considered in this paper differ in the level of coordination employed, ranging from no coordination to complete coordination. The strategy structure in all cases is shown to be threshold-based, and the thresholds which are analytically derived in this paper can be calculated offline, resulting in a very low online computational load. The analysis is extended to the case where coordination is supplied by a self-interested monopolist communication provider, charging a fee that depends on the number of agents for which coordination is required. In this case, the agents' expected-benefit-maximizing cooperative exploration strategy is to have some sub-groups coordinate their exploration (if at all) while the remaining agents explore individually with no coordination between them. We show that given the option for side-payments, the exploring agents can improve their expected benefit by compensating the communication provider to change the price at which she offers her services. An illustration for the importance of considering others' findings in one's strategy is given using the spectrum sensing application, experimenting with real data.

A Pareto-efficient and fair mediation approach to multilateral negotiation

Abstract: 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 this problem, we propose a mediated negotiation approach to support the agents reaching an efficient and fair agreement in multi-party multi-issue negotiation. The proposed approach improves the agents' utility values from the status quo, by searching for the mutually preferred outcomes that minimizes the difference between the agents' utility gains, leading to fair agreements. We present two case studies to illustrate the capability of the proposed approach in real-world negotiation applications. We also provide an experimental evaluation of the overall performance of our proposed approach. The experimental results demonstrate that out proposed approach does not only guarantee Pareto-efficiency, but also produces outcomes that are close to the fair egalitarian solutions.

Truthful and efficient mechanisms for Website dependent advertising auctions

Abstract: Recently we have witnessed the phenomena of private Website owners who are willing to dedicate space on their Website for advertisements managed by leading search engines (e.g., Google, Bing and Yahoo). In most cases the choice of the advertisements displayed on a certain Website is made without taking into account the preferences of the Website hosting the advertisements. This causes the Website that dedicate space for the ads to be exposed to ads that are irrelevant to the content on the Website. In this paper, we focus on the design of auction protocols that take into account the Website owner's preferences by associating him with a utility function reflecting the value for each ad shown in his space. In doing so we introduce the dispensation scheme into the second price sealed bid auction for both the single and the multi-slot cases. For the single-slot, we propose a mechanism that proved to be individual rational, truthful, and a free advertisement condition is defined. For the multi-slot case, we propose three truthful mechanisms. Simulation results show that the allocation efficiency of two of the proposed mechanisms maintain a near to optimal allocation efficiency compared to optimal allocation calculated using the Hungarian mechanism, while substantially reducing computational complexity from cubic to linear.

Intention management within a BDI framework

Abstract: The Belief-Desire-Intention (BDI) model of agency provides a powerful technique for describing goal-based behavior for both individual agents and, more recently, agent teams. Numerous frameworks have been developed since the model was first proposed in the early 1980's. However, none of these frameworks have explicitly represented intention, which has meant that intention-based reasoning has had no direct framework support. Given the importance of this in the development of practical agent applications, we consider this to be a major shortcoming of existing frameworks. This paper explores how explicitly represented goals can be used as both a unifying modeling concept for the management of intention, and as the basis for a BDI framework. The exploration is grounded both in terms of software – a recently developed BDI framework called GORITE and in application – an execution system for a robotic assembly cell. Both are discussed in detail.

A dynamic hybrid buyer bidding strategy for decentralized and cloud-based many-to-many negotiation

Abstract: The decentralized many-to-many negotiation for resource allocation in Cloud and multi-agent systems presents numerous challenges, including ones related to the buyer strategy which is the focus of the present paper Current approaches deriving required resources each bid must ask for aren't in all market cases an optimal choice For this reason, we have proposed a hybrid negotiation strategy consisting of a combination of two modes of negotiation strategies that generates required resources of each bid in parallel, the first one is an existent fixed negotiation strategy and the second one is a learning selection strategy over the buyer's agreement space Moreover, acting dynamically in the market place by adjusting appropriately the buyer's resource provisioning times and calling for proposal to hand over contracted resources in order to break some deadlocks involving buyers' tasks has been shown via simulation results to achieve better performances both in terms of social welfare and buyer utility

Reliable fault tolerant model for grid computing environments

Abstract: Grid reliability analysis and modeling are not easy tasks because of the complexity and large scale of the system. For some grid services which have large subtasks requiring time-consuming computation, the reliability of grid service could be rather low. To resolve this problem, RNFR and LNFR are proposed in literature. This paper describes the property of the grid computing systems and analyzes the grid program and service reliability. In this paper, we propose a fault tolerance mechanism, namely LRNFR, based both on RNFR and LNFR in a complementary manner with a periodic migration. We select the most reliable node among the set of Neighboring Collaborators. The migration process is divided by the MDTTR of the failed node until its repair or the migration of all its programs. Experiments demonstrate the performance of the proposed approach.

A framework for context-aware web service composition using planning techniques

Abstract: A web service is an application that is published on the web and can be discovered and used automatically. In many cases, a web service cannot provide the capability that the user has requested. Therefore, according to the user request, it should be possible to combine various services and produce a new composite service for user request. AI planning techniques are used for automated web service composition. Also, context is the information that can be used to characterize the situation of an entity. JSHOP2 is one of the techniques of planning. In this paper, the design and implementation of the proposed framework for context-aware web service composition is presented and is used JSHOP2 and the proposed framework reduces the number of failures and composition time.

Design of a multi-agent opportunistic grid computing platform

Abstract: Opportunistic grid computing is an emergent paradigm that combines idle volunteer nodes from enterprises in different geographic locations into a cost effective, converged high performance commodity computing grid. This paper presents the MAOG design; an implementation process for an infrastructure optimized for sharing computational cycles and disk space from commodity computers utilizing Multi-Agent Systems. The proposed approach brings transparent and pervasive grid user access to resources which would otherwise not be available to their disposal. An appraisal of the code mobility model to be utilized for the MAOG design in two phases (Mobile Agent and Remote Evaluation design paradigms), adopting the Contract Net Protocol is analyzed. This paper presents in detail, the main components that make up the Mobile Agent design, including the message passing model for achieving the specified service objectives.

A geometric model for website evolution in mobile internet

Abstract: This paper studies website evolution in mobile Internet. In particular, mobile user behaviors are employed to geometrically model website's developmental status and trend and to understand the comprehensive strength of websites. First, a website evolution model is proposed that is defined using three model parameters, namely, user ensemble size, user acceptance and user loyalty. Then, algorithms of calculating the evolution model parameters based on mobile user behavior attributes are presented. Next, geometric charting of the website evolution model in mobile Internet is established in terms of website developmental space to visualize the website evolution. Finally, using real data collected from a major Mobile Telecom Operator, geometric analysis on website evolution is conducted to exhibit the comprehensive strength of the websites and to validate the proposed website evolution model.