Cost Based Optimization of Job Allocation in Computational Grids

Computational grids are distributed systems composed of heterogeneous computing resources which are distributed geographically and administratively. These highly scalable systems are designed to meet the large computational demands of many users from scientific and business orientations. Grid computing is a powerful concept, its chief appeal being the ability to make sure all of a resource’s computing power is used. In a grid world, the idle time of hundreds or thousands of resources could be harnessed and rented out to anyone who needed a massive infusion of processing power. First, the architecture of a grid system is presented. The design gives a mathematical model of the grid system for efficiently allocating the grids resources. The challenges faced for optimal job allocation motivate the exploration in optimizing grid resource allocations. We have extensively surveyed the current state of art in this area. A grid server coordinates the job allocation for the grid users and helps to select the best resources for a job among different possible resource offers with the best prices offered. Interaction between grid users and the resources require a mediator that uses different paradigm to communicate the needs of the two parties in terms of performance requirements, timing constraints, price charged etc. A game theoretic bargaining approach is studied to agree upon standard prices. We have implemented various job allocation schemes in computational grids based on the mathematical modeling of the grid system and bargaining protocol with the objective function of optimizing the cost. The performance of the schemes have been analyzed and compared. A new model for job allocation in computational grids has been proposed, for job allocation based on the clustering of resources

Channel assignment and routing in cooperative and competitive wireless mesh networks

This thesis was submitted for the degree of Docter of Philosophy and awarded by Brunel University.In this thesis, the channel assignment and routing problems have been investigated for both cooperative and competitive Wireless Mesh networks (WMNs). A dynamic and distributed channel assignment scheme has been proposed which generates the network topologies ensuring less interference and better connectivity. The proposed channel assignment scheme is capable of detecting the node failures and mobility in an efficient manner. The channel monitoring module precisely records the quality of bi-directional links in terms of link delays. In addition, a Quality of Service based Multi-Radio Ad-hoc On Demand Distance Vector (QMR-AODV) routing protocol has been devised. QMR-AODV is multi-radio compatible and provides delay guarantees on end-to-end paths. The inherited problem of AODV’s network wide flooding has been solved by selectively forwarding the routing queries on specified interfaces. The QoS based delay routing metric, combined with the selective route request forwarding, reduces the routing overhead from 24% up to 36% and produces 40.4% to 55.89% less network delays for traffic profiles of 10 to 60 flows, respectively. A distributed channel assignment scheme has been proposed for competitive WMNs, where the problem has been investigated by applying the concepts from non-cooperative bargaining Game Theory in two stages. In the first stage of the game, individual nodes of the non-cooperative setup is considered as the unit of analysis, where sufficient and necessary conditions for the existence of Nash Equilibrium (NE) and Negotiation-Proof Nash Equilibrium (N-PNE) have been derived. A distributed algorithm has been presented with perfect information available to the nodes of the network. In the presence of perfect information, each node has the knowledge of interference experience by the channels in its collision domain. The game converges to N-PNE in finite time and the average fairness achieved by all the nodes is greater than 0.79 (79%) as measured through Jain Fairness Index. Since N-PNE and NE are not always a system optimal solutions when considered from the end-nodes prospective, the model is further extended to incorporate non-cooperative end-users bargaining between two end user’s Mesh Access Points (MAPs), where an increase of 10% to 27% in end-to-end throughput is achieved. Furthermore, a non-cooperative game theoretical model is proposed for end-users flow routing in a multi-radio multi-channel WMNs. The end user nodes are selfish and compete for the channel resources across the WMNs backbone, aiming to maximize their own benefit without taking care for the overall system optimization. The end-to-end throughputs achieved by the flows of an end node and interference experienced across the WMNs backbone are considered as the performance parameters in the utility function. Theoretical foundation has been drawn based on the concepts from the Game Theory and necessary conditions for the existence of NE have been extensively derived. A distributed algorithm running on each end node with imperfect information has been implemented to assess the usefulness of the proposed mechanism. The analytical results have proven that a pure strategy Nash Equilibrium exists with the proposed necessary conditions in a game of imperfect information. Based on a distributed algorithm, the game converges to a stable state in finite time. The proposed game theoretical model provides a more reasonable solution with a standard deviation of 2.19Mbps as compared to 3.74Mbps of the random flow routing. Finally, the Price of Anarchy (PoA) of the system is close to one which shows the efficiency of the proposed scheme.The Higher Education Commission of Pakistan and the University of Engineering and Technology, Peshawar

Modified bargaining protocols for automated negotiation in open multi-agent systems

Current research in multi-agent systems (MAS) has advanced to the development of open MAS, which are characterized by the heterogeneity of agents, free exit/entry and decentralized control. Conflicts of interest among agents are inevitable, and hence automated negotiation to resolve them is one of the promising solutions. This thesis studies three modifications on alternating-offer bargaining protocols for automated negotiation in open MAS. The long-term goal of this research is to design negotiation protocols which can be easily used by intelligent agents in accommodating their need in resolving their conflicts. In particular, we propose three modifications: allowing non-monotonic offers during the bargaining (non-monotonic-offers bargaining protocol), allowing strategic delay (delay-based bargaining protocol), and allowing strategic ignorance to augment argumentation when the bargaining comprises argumentation (ignorance-based argumentation-based negotiation protocol). Utility theory and decision-theoretic approaches are used in the theoretical analysis part, with an aim to prove the benefit of these three modifications in negotiation among myopic agents under uncertainty. Empirical studies by means of computer simulation are conducted in analyzing the cost and benefit of these modifications. Social agents, who use common human bargaining strategies, are the subjects of the simulation. In general, we assume that agents are bounded rational with various degrees of belief and trust toward their opponents. In particular in the study of the non-monotonic-offers bargaining protocol, we assume that our agents have diminishing surplus. We further assume that our agents have increasing surplus in the study of delay-based bargaining protocol. And in the study of ignorance-based argumentation-based negotiation protocol, we assume that agents may have different knowledge and use different ontologies and reasoning engines. Through theoretical analysis under various settings, we show the benefit of allowing these modifications in terms of agents’ expected surplus. And through simulation, we show the benefit of allowing these modifications in terms of social welfare (total surplus). Several implementation issues are then discussed, and their potential solutions in terms of some additional policies are proposed. Finally, we also suggest some future work which can potentially improve the reliability of these modifications

Channel assignment and routing in cooperative and competitive wireless mesh networks

In this thesis, the channel assignment and routing problems have been investigated for both cooperative and competitive Wireless Mesh networks (WMNs). A dynamic and distributed channel assignment scheme has been proposed which generates the network topologies ensuring less interference and better connectivity. The proposed channel assignment scheme is capable of detecting the node failures and mobility in an efficient manner. The channel monitoring module precisely records the quality of bi-directional links in terms of link delays. In addition, a Quality of Service based Multi-Radio Ad-hoc On Demand Distance Vector (QMR-AODV) routing protocol has been devised. QMR-AODV is multi-radio compatible and provides delay guarantees on end-to-end paths. The inherited problem of AODV’s network wide flooding has been solved by selectively forwarding the routing queries on specified interfaces. The QoS based delay routing metric, combined with the selective route request forwarding, reduces the routing overhead from 24% up to 36% and produces 40.4% to 55.89% less network delays for traffic profiles of 10 to 60 flows, respectively. A distributed channel assignment scheme has been proposed for competitive WMNs, where the problem has been investigated by applying the concepts from non-cooperative bargaining Game Theory in two stages. In the first stage of the game, individual nodes of the non-cooperative setup is considered as the unit of analysis, where sufficient and necessary conditions for the existence of Nash Equilibrium (NE) and Negotiation-Proof Nash Equilibrium (N-PNE) have been derived. A distributed algorithm has been presented with perfect information available to the nodes of the network. In the presence of perfect information, each node has the knowledge of interference experience by the channels in its collision domain. The game converges to N-PNE in finite time and the average fairness achieved by all the nodes is greater than 0.79 (79%) as measured through Jain Fairness Index. Since N-PNE and NE are not always a system optimal solutions when considered from the end-nodes prospective, the model is further extended to incorporate non-cooperative end-users bargaining between two end user’s Mesh Access Points (MAPs), where an increase of 10% to 27% in end-to-end throughput is achieved. Furthermore, a non-cooperative game theoretical model is proposed for end-users flow routing in a multi-radio multi-channel WMNs. The end user nodes are selfish and compete for the channel resources across the WMNs backbone, aiming to maximize their own benefit without taking care for the overall system optimization. The end-to-end throughputs achieved by the flows of an end node and interference experienced across the WMNs backbone are considered as the performance parameters in the utility function. Theoretical foundation has been drawn based on the concepts from the Game Theory and necessary conditions for the existence of NE have been extensively derived. A distributed algorithm running on each end node with imperfect information has been implemented to assess the usefulness of the proposed mechanism. The analytical results have proven that a pure strategy Nash Equilibrium exists with the proposed necessary conditions in a game of imperfect information. Based on a distributed algorithm, the game converges to a stable state in finite time. The proposed game theoretical model provides a more reasonable solution with a standard deviation of 2.19Mbps as compared to 3.74Mbps of the random flow routing. Finally, the Price of Anarchy (PoA) of the system is close to one which shows the efficiency of the proposed scheme.EThOS - Electronic Theses Online ServiceHigher Education Commission of PakistanUniversity of Engineering and Technology, PeshawarGBUnited Kingdo

Mobile-agent based multi-constraint one-to-many bilateral e-Negotiation framework

The thesis proposes a multi-constraint one-to-many bilateral e-Trade negotiation framework. It deploys mobile agents in negotiation, considers trading competition between vendors and search space, efficiently manages the risk of losing top utility offers that expire before the negotiation deadline, accurately evaluates offers, and truly maintains the security of negotiation data