18067929
Multiagent SAT (MASSAT): Autonomous Pattern Search in Constrained Domains
In this paper, we present an autonomous pattern search approachto solving Satisfiability Problems (SATs). Our approach is essentially a multiagent system. To solve a SAT problem, we first divide variables into groups, and represent each variable group with an agent. Then, we randomly place each agent onto a position in the correspoding local space which is composed of the domains of the variables that are represented by this agent. Thereafter, all agents will autonomously make searchdecisions guided by some reactive rules in their local spaces until a special pattern (i.e., solution) is found or a time step threshold is reached. Experimental results on some benchmark SAT test-sets have shown that by employing the MASSAT approach, we can obtain performances comparable to those of other popular algorithms.
33842812
Anycast-Based Cooperative Proxy Caching
As one of the most popular applications currently running on the Internet, the World Wide Web is of an exponential growth in size, which results in the network congestion and server overloading. Web caching as an important technique aims at reducing network traffic, server load, and user-perceived retrieval delays by replicating popular contents on proxy caches. In our paper, we develop an anycast-based cooperative web proxy caching mechanism. It puts response time, hop counts, self-organized load balancing, adaption, and self-configuration as primary concerns. In our scheme, anycast is used to bring a server “nearest” to a client to improve overall performance, all proxies in a local network consists an anycast group. The object placement and replacement problems are formulated as an optimization problem and the solution is obtained by using an anycast-based cooperative proxy caching algorithm. Some simulation experiments have been conduced to evaluate the proposed scheme in terms of a wide range of performance metrics. Analytical and experimental results show that our algorithm outperforms some existing algorithms in response time, hop counts.
37149853
New Challenges in the World Wide Wisdom Web (W4) Research
This talk addresses the research and development needs for creating the new paradigm shift in Internet computing. In particular, it presents a promising answer to such needs, called the World Wide Wisdom Web (W4), and identifies several research challenges and enabling technologies in developing the W4.
41297506
Evolutionary Negotiation in Agent-Mediated Commerce
Automated negotiation has become increasingly important since the advent of electronic commerce. In an efficient market, goods are not necessarily traded in a fixed price, and instead buyers and sellers negotiate among themselves to reach a deal that maximizes the payoffs of both parties. In this paper, a genetic agent-based model for bilateral, multi-issue negotiation is studied. The negotiation agent employs genetic algorithms and attempts to learn its opponent's preferences according to the history of the counter offers based upon the stochastic approximation. We also consider two types of agents: level- 0 agents are only concerned with their own interest while level-1 agents consider also their opponents' utility. Our goal is to develop an automated negotiator that guides the negotiation process so as to maximize both parties' payoff.
15907163
Characterizing Web usage regularities with information foraging agents
Researchers have recently discovered several interesting, self-organized regularities from the World Wide Web, ranging from the structure and growth of the Web to the access patterns in Web surfing. What remains to be a great challenge in Web log mining is how to explain user behavior underlying observed Web usage regularities. We address the issue of how to characterize the strong regularities in Web surfing in terms of user navigation strategies, and present an information foraging agent-based approach to describing user behavior. By experimenting with the agent-based decision models of Web surfing, we aim to explain how some Web design factors as well as user cognitive factors may affect the overall behavioral patterns in Web usage.
5220045
A study of the performance and parameter sensitivity of adaptive distributed caching
A self-organized approach to manage a distributed proxy system called Adaptive Distributed Caching (ADC) has been proposed previously [8]. We model each proxy as an autonomous agent that is equipped to decide how to deal with client requests using local information. Experimental results show that our ADC algorithm is able to compete with typical hashing-based approaches. This paper gives a full description of the self-organizing distributed algorithm, with a performance comparison based on hits and hops rate. Additional evaluation of the parameters caching-, multiple- and single-table size is also presented.
195860670
Optimal stream replication for video simulcasting
Video simulcasting enables a sender to generate multiple streams for the same video program but at different rates, targeting receivers of different capacities. Each stream can then be distributed to the target receivers via broadcast or multicast channels. One of the critical issues in video simulcasting is to strike a balance between bandwidth consumption and the user satisfaction. This is because stream replication introduces redundancy which can potentially lead to excessive use of the bandwidth, while on the other hand there usually is a mismatch between a receiver's capacity and the limited choice of the stream bandwidths. We present a formal study on the above issue, which we refer as the optimal stream replication problem. We first formulate the optimal replication problem for a given session bandwidth budget and number of streams, with the objective of minimizing the expected mismatch for all the receivers in the session. A proper choice for the number of the replicated streams is critical in the overall bandwidth provisioning. Though it has been largely assumed that the number of streams is predetermined by service providers, we find that dynamic adjustment of stream number is possible in advanced video stream systems, such as the MPEG-4 Delivery Multimedia Integration Framework (DIMF), and systems employing fast video transcoding algorithms. Therefore, we also study the case of a flexible stream number, with the objective of jointly optimize the stream number and bandwidth allocated to each stream.
1787760
Greedy is Good: On Service Tree Placement for In-Network Stream Processing
This paper is concerned with reducing communication costs when executing distributed user tasks in a sensor network. We take a service-oriented abstraction of sensor networks, where a user task is composed of a set of data processing modules (called services) with dependencies. Communications in sensor networks consume significant energy and introduce uncertainty in data fidelity due to high bit error rate. These constraints are abstracted as costs on the communication graph. The goal is to place the services within the sensor network so that the communication cost in performing the task is minimized. In addition, since the lifetime of a node, the quality of network links, and the composition of the service graph may change over time, the quality of the placement must be maintained in the face of these dynamics. In this paper, we take a fresh look at what is generally considered a simple but poor performance approach for service placement, namely the greedy algorithm. We prove that a modified greedy algorithm is guaranteed to have cost at most 8 times the optimum placement. In fact, the guarantee is even stronger if there is a high degree of data reduction in the service graph. The advantage of the greedy placement strategy is that when there are local changes in the service graph or when a hosting node fails, the repair only affects the placement of services that depend on the changes. Simulations suggest that in practice the greedy algorithm finds a low cost placement. Furthermore, the cost of repairing a greedy placement decreases rapidly as a function of the proximity of the services to be aggregated.
15698160
Performance prediction of a parallel simulator
There are at least three major obstacles thwarting widespread adoption of parallel discrete-event simulation: lack of need; lack of tools; and lack of predictability in behavior and performance. The plain truth is that most simulation studies can be adequately done on ordinary serial computers. Parallel simulation tools are products of research efforts, and simply do not stand up to the demands of modern software engineering. The results of 20 years of research in parallel simulation reveal it to be a highly complex endeavour, with performance results very much dependent on implementation details and model characteristics. The Scalable Simulation Framework (SSF) is an effort to address some these concerns. It addresses lack of need in two ways; it provides a modeling API that is attractive both for serial and parallel simulation, with parallel execution requiring no change to the model, and it targets large-scale telecommunication system modeling, an application area that requires the computational capabilities of parallelism. We address the concern over unpredictable behavior. We show how we measured the internal overheads of the Dartmouth implementation of the SSF API (DaSSF), and how those measurements can be used to predict the performance of a given model, using given features of the simulator, without having to run, or even build, the model.
1410914
Collective problem solving through coordinated reaction
We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), for collective, evolutionary problem solving. Problem solving is viewed as an emergent functionality from the evolving process of a group of diverse, interacting, and well-coordinated reactive agents. Cheap and effective search knowledge is extracted from local interactions and embedded in the coordination mechanism. Our domain of problem solving is constraint satisfaction problems. We have applied the methodology to job shop scheduling, an NP-complete constraint satisfaction problem. Experimental results on a benchmark suite of problems show that CP&CR outperformed three other state-of-the-art direct search scheduling techniques, in both efficiency and number of problems solved. In addition, CP&CR was experimentally tested on problems of larger sizes and showed favorable scaling-up characteristics.<<ETX>>
911649
Emergent Constraint Satisfaction Through Multi-Agent Coordinated Interaction
We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), for distributed constraint satisfaction based on partitioning the set of constraints into subsets of different constraint types. Associated with each constraint type is a set of specialised agents, each of which is responsible for enforcing constraints of the specified type for the set of variables under its jurisdiction. Variable instantiation is the joint responsibility of a set of agents, each of which has a different perspective on the instantiation according to a particular constraint type and can revise the instantiation in response to violations of the specific constraint type. The final solution emerges through incremental local revisions of an initial, possibly inconsistent, instantiation of all variables. Solution revision is the result of coordinated local reaction of the specialised constraint agents. We have applied the methodology to job shop scheduling, an NP-complete constraint satisfaction problem. Utility of different types of coordination information in CP&CR was investigated. In addition, experimental results on a benchmark suite of problems show that CP&CR performed considerably well as compared to other centralised search scheduling techniques, in both computational cost and number of problems solved.