Bjorn Landfeldt

Game-Theoretic Approach for Load Balancing in Computational Grids

Load balancing is a very important and complex problem in computational grids. A computational grid differs from traditional high-performance computing systems in the heterogeneity of the computing nodes, as well as the communication links that connect the different nodes together. There is a need to develop algorithms that can capture this complexity yet can be easily implemented and used to solve a wide range of load-balancing scenarios. In this paper, we propose a game-theoretic solution to the grid load-balancing problem. The algorithm developed combines the inherent efficiency of the centralized approach and the fault-tolerant nature of the distributed, decentralized approach. We model the grid load-balancing problem as a noncooperative game, whereby the objective is to reach the Nash equilibrium. Experiments were conducted to show the applicability of the proposed approaches. One advantage of our scheme is the relatively low overhead and robust performance against inaccuracies in performance prediction information.

SLM, a framework for session layer mobility management

This paper describes a novel framework for managing connections to mobile hosts in the Internet. The framework, SLM, integrates the notions of quality of service management and mobility management and forms a base for overall session management. We compare SLM with the currently most widely adopted mobility management framework, Mobile IP, and show how some of Mobile IPs deficiencies are overcome. The paper further presents some initial experimental results and future research.

Artificial life techniques for load balancing in computational grids

Load balancing is a very important and complex problem in computational grids. A computational grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes and communication links, as well as background workloads that may be present in the computing nodes. There is a need to develop algorithms that could capture this complexity yet can be easily implemented and used to solve a wide range of load balancing scenarios. Artificial life techniques have been used to solve a wide range of complex problems in recent times. The power of these techniques stems from their capability in searching large search spaces, which arise in many combinatorial optimization problems, very efficiently. This paper studies several well-known artificial life techniques to gauge their suitability for solving grid load balancing problems. Due to their popularity and robustness, a genetic algorithm (GA) and tabu search (TS) are used to solve the grid load balancing problem. The effectiveness of each algorithm is shown for a number of test problems, especially when prediction information is not fully accurate. Performance comparisons with Min-min, Max-min, and Sufferage are also discussed.

MARCH: a distributed content adaptation architecture

A novel, server-centric architecture for adapting media content to suit the operational environment for heterogeneous devices and networks is presented. The given architecture, so called MARCH, exhibits several advantages over traditional static proxy solutions. The viability of the MARCH framework has been demonstrated through a prototype implementation.

Cooperative power-aware scheduling in grid computing environments

Energy usage and its associated costs have taken on a new level of significance in recent years. Globally, energy costs that include the cooling of server rooms are now comparable to hardware costs, and these costs are on the increase with the rising cost of energy. As a result, there are efforts worldwide to design more efficient scheduling algorithms. Such scheduling algorithm for grids is further complicated by the fact that the different sites in a grid system are likely to have different ownerships. As such, it is not enough to simply minimize the total energy usage in the grid; instead one needs to simultaneously minimize energy usage between all the different providers in the grid. Apart from the multitude of ownerships of the different sites, a grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes as well as the communication links that connect the different nodes together. In this paper, we propose a cooperative, power-aware game theoretic solution to the job scheduling problem in grids. We discuss our cooperative game model and present the structure of the Nash Bargaining Solution. Our proposed scheduling scheme maintains a specified Quality of Service (QoS) level and minimizes energy usage between all the providers simultaneously; energy usage is kept at a level that is sufficient to maintain the desired QoS level. Further, the proposed algorithm is fair to all users, and has robust performance against inaccuracies in performance prediction information.

Trust-Based Fast Authentication for Multiowner Wireless Networks

In multiowner wireless networks, access points (APs) are owned and operated by different administrations, leading to significant authentication delays during handoff between APs. We propose to exploit the trust between the owners of neighboring APs for reducing the authentication delay. In the proposed authentication scheme, neighboring APs that trust each other share the security key for the visiting node to avoid lengthy authentication routines each time the visiting node switches APs. The performance of the proposed trust-based authentication scheme is evaluated using a Markov model. Using numerical experiments, we first study a basic scenario where mobile nodes are not aware of the trust networks that exist in a given neighborhood. Subsequently, we consider an advanced scenario where a mobile node functionality is augmented to discover the trust network so as to minimize roaming beyond the trusted APs. We find that, even with the basic implementation, the average number of full authentications needed for a roaming mobile reduces linearly as the likelihood of two neighboring APs trusting each other increases. With the advanced implementation, our experiments show that quadratic reduction is achieved. The Markov model is validated using discrete event simulation.

Multiclass G/M/1 queueing system with self-similar input and non-preemptive priority

The Internet domains are tied together by service level agreements which are based on various QoS parameters such as delay, jitter, packet-loss rate, throughput and availability. To offer tighter and more comprehensive service level agreements, accurate modeling of IP traffic and its queuing behavior over the entire network domain is necessary. We present a novel analytical model of a single router which takes into account multiple classes of self-similar traffic based on G=M=1 queueing system with non-preemptive priority. Our long-range dependent traffic model is generated by infinitely many sources governed by a Poisson random measure. We derive exact expressions for the transition probabilities of the embedded Markov chain of G=M=1 by first deriving the interarrival distribution of the incoming traffic. Closed form expressions for the expected waiting time of multiple classes have been derived. The queuing system is evaluated numerically for a typical router to show the effect of the Hurst parameter on several performance measures. Such work forms a basis for modeling the behavior of self-similar traffic accurately through heterogenous network domains, eventually leading to the formation of realistic service level agreements. (Less)

Experiences in deploying a wireless mesh network testbed for traffic control

Wireless mesh networks (WMN) have attracted considerable interest in recent years as a convenient, flexible and low-cost alternative to wired communication infrastructures in many contexts. However, the great majority of research on metropolitan-scale WMN has been centered around maximization of available bandwidth, suitable for non-real-time applications such as Internet access for the general public. On the other hand, the suitability of WMN for mission-critical infrastructure applications remains by and large unknown, as protocols typically employed in WMN are, for the most part, not designed for real-time communications. In this paper, we describe the Smart Transport and Roads Communications (STaRComm) project at National ICT Australia (NICTA), which sets a goal of designing a wireless mesh network architecture to solve the communication needs of the traffic control system in Sydney, Australia. This system, known as SCATS (Sydney Coordinated Adaptive Traffic System)and used in over 100 cities around the world, connects a hierarchy of several thousand devices -- from individual traffic light controllers to regional computers and the central Traffic Management Centre (TMC)-- and places stringent requirements on the reliability and latency of the data exchanges. We discuss our experience in the deployment of an initial testbed consisting of 7 mesh nodes placed at intersections with traffic lights, and share the results and insights learned from our measurements and initial trials in the process.

An analysis of a modified point coordination function in IEEE 802.11

Since the point coordination function (PCF) in the IEEE 802.11 is based on a centralized polling protocol, some bandwidth is wasted due to the polling overheads and also due to null packets that are issued in case a polled station does not have any data to transmit. In order to reduce this waste and increase the channel utilization, we have proposed a modified version of the standard PCF. The modified PCF uses a distributed polling protocol (DPP) as the access mechanism for the uplink transmission of real-time traffic. The transmission period in the modified PCF consists of a distributed polling protocol period (DPPP) which is controlled by the DPP and the real-time traffic downlink period (KTDP). Our proposal further includes a technique for dealing with the hidden station problem for use together with the proposed modification. In this paper, an analysis is done to compare the performance of the modified PCF with the standard PCF in terms of number of supportable stations in a contention-free period (CFP) and the channel efficiency. The analytical results show that the modified PCF can support a much higher number of stations than the standard PCF. In addition, the channel efficiency of the modified PCF is better under the assumption that there is no hidden station in the system. The results imply that the channel utilization of the modified PCF is better than the standard PCF.

Service level agreements (SLAs) parameter negotiation between heterogeneous 4G wireless network operators

Abstract We are currently witnessing a growing interest of network operators to migrate their existing 2G/3G networks to 4G technologies such as long-term evolution (LTE) to enhance the user experience and service opportunities in terms of providing multi-megabit bandwidth, more efficient use of radio networks, latency reduction, and improved mobility. Along with this, there is a strong deployment of packet data networks such as those based on IEEE 802.11 and 802.16 standards. Mobile devices are having increased capabilities to access many of these wireless networks types at the same time. Reinforcing quality of service (QoS) in 4G wireless networks will be a major challenge because of varying bit rates, channel characteristics, bandwidth allocation and global roaming support among heterogeneous wireless networks. As a mobile user moves across access networks, to the issue of mapping resource reservations between different networks to maintain QoS behavior becomes crucial. To support global roaming and interoperability across heterogeneous wireless networks, it is important for wireless network operators to negotiate service level agreement (SLA) contracts relevant to the QoS requirements. Wireless IP traffic modeling (in terms of providing assured QoS) is still immature because the majority of the existing work is merely based on the characterization of wireless IP traffic without investigating the behavior of queueing systems for such traffic. To overcome such limitations, we investigate SLA parameter negotiation among heterogeneous wireless network operators by focusing on traffic engineering and QoS together for 4G wireless networks. We present a novel mechanism that achieves service continuity through SLA parameter negotiation by using a translation matrix, which maps QoS parameters between different access networks. The SLA matrix composition is modeled analytically based on the G/M/1 queueing system. We evaluate the model using two different scheduling schemes and we derive closed form expressions for different QoS parameters for performance metrics such as packet delay and packet loss rate. We also develop a discrete event simulator and conduct a series of simulation experiments in order to understand the QoS behavior of corresponding traffic classes.