Improving job scheduling performance with parallel access to replicas in Data Grid environment

Data Grid has evolved to be the solution for data-intensive applications, such as High Energy Physics (HEP), astrophysics, and computational genomics. These applications usually have large input of data to be analyzed and these input data are widely replicated across Data Grid to improve the performance. The job scheduling performance on traditional computing jobs can be studied using queuing theory. However, with the addition of data transfer, the job scheduling performance is too complex to be modeled. In this research, we study the impact of data transfer on the performance of job scheduling in the Data Grid environment. We have proposed a parallel downloading system that supports replicating data fragments and parallel downloading of replicated data fragments, to improve the job scheduling performance. The performance of the parallel downloading system is compared with non-parallel downloading system, using three scheduling heuristics: Shortest Turnaround Time (STT), Least Relative Load (LRL) and Data Present (DP). Our simulation results show that the proposed parallel download approach greatly improves the Data Grid performance for all three scheduling algorithms, in terms of the geometric mean of job turnaround time. The advantage of parallel downloading system is most evident when the Data Grid has relatively low network bandwidth and relatively high computing power.     

Effectiveness of Explicit Stations Grouping in Crowded Wireless LANs

In this letter, we evaluate the effectiveness of a multi-stage contention scheme for wireless local area networks (WLANs) medium access control (MAC). Multi-stage contention schemes basically divide the stations into smaller groups to resolve the contention more efficiently. Previous researchers have proposed virtual grouping schemes for WLANs MAC. Here we quantitatively analyze what can be achieved with a simple grouping scheme, i.e. through multi-stage contention. Our analysis shows that the multi-stage scheme is efficient in resolving contention, making it a good alternative to the commonly used exponential backoff mechanism.     

A fuzzy neural network with fuzzy impact grades

Fuzzy rule derivation is often difficult and time-consuming, and requires expert knowledge. This creates a common bottleneck in fuzzy system design. In order to solve this problem, many fuzzy systems that automatically generate fuzzy rules from numerical data have been proposed. In this paper, we propose a fuzzy neural network based on mutual subsethood (MSBFNN) and its fuzzy rule identification algorithms. In our approach, fuzzy rules are described by different fuzzy sets. For each fuzzy set representing a fuzzy rule, the universe of discourse is defined as the summation of weighted membership grades of input linguistic terms that associate with the given fuzzy rule. In this manner, MSBFNN fully considers the contribution of input variables to the joint firing strength of fuzzy rules. Afterwards, the proposed fuzzy neural network quantifies the impacts of fuzzy rules on the consequent parts by fuzzy connections based on mutual subsethood. Furthermore, to enhance the knowledge representation and interpretation of the rules, a linear transformation from consequent parts to output is incorporated into MSBFNN so that higher accuracy can be achieved. In the parameter identification phase, the backpropagation algorithm is employed, and proper linear transformation is also determined dynamically. To demonstrate the capability of the MSBFNN, simulations in different areas including classification, regression and time series prediction are conducted. The proposed MSBFNN shows encouraging performance when benchmarked against other models.     

Semantics in service discovery and QoS measurement

For the vision of ubiquitous, easily invokable Web services to become a reality, it will be necessary for service requesters to compare the quality-of-service (QoS) aspects of various services. So standardized QoS information must become a part of the service discovery process. This article surveys the current research on QoS and service discovery, including ontologies such as OWL-S and DAML-S. The authors then propose their own ontology, DAML-QoS, which provides detailed QoS information in a DAML format.     

A Hybrid Analysis of an Optimization Approach for Cluster Applications

Cluster/distributed computing has become a popular, cost-effective alternative to high-performance parallel computers. Many parallel programming languages and related programming models have become widely accepted on clusters. However, the high communication overhead is a major shortcoming of running parallel applications on cluster/distributed computing environments. To reduce the communication overhead and thus the completion time of a parallel application, this paper introduces and evaluates an efficient Key Message (KM) approach to support parallel computing on cluster computing environments. In this paper, we briefly present the model and algorithm, and then analytical and simulation methods are adopted to evaluate the performance of the algorithm. It demonstrates that when network background load increases or the computation to communication ratio decreases, the analysis results show better improvement on communication of a parallel application over the system which does not use the KM approach.     

Optimal algorithm for scheduling CBR traffic in ATM switches

A non-blocking input buffered ATM switch that supports CBR and ABR traffic using a TDM scheduler frame is considered. A new TDM scheduler algorithm (largest-first) for CBR traffic is compared with four others, based on the evenness of the distribution of unused timeslots in the scheduling frame. An even distribution of unused slots minimises the average latency and jitter for ABR traffic. Simulation results show that largest-first allocation is the best     

Design and Implementation of a Java-based Meeting Space over Internet

This paper describes the implementation of Java Meeting Space (JMS), a generic, extensible framework and environment for developing synchronous collaborative applications. The JMS framework is based on a fully object-oriented replicated architecture where the application instances and management services are all replicated at each site. JMS provides basic CSCW coordination services: session management and dynamic floor control services. As a framework, it provides a set of programming interfaces that allow an application developer to take advantage of coordination services in the runtime environment.     

A terminal-assisted route optimized NEMO management

The NEMO basic support protocol enhances mobile IPv6 (MIPv6) to enable mobile router (MR) to move together with mobile network node (MNN) as a unit. This protocol suffers from pinball routing effect which has triggered research works to enable direct routing between MNNs in the presence of network mobility. Instead of relying on MIPv6, this paper describes network mobility using a novel terminal-assisted IP mobility protocol on MNNs that work cooperatively with MRs and access routers to provide seamless connectivity. This protocol is superior as it neither suffers from pinball routing effect nor requires dedicated infrastructure support such as home agent. It also eliminates the need to dynamically increase the size of IP header in IP tunneling. Through quantitative comparisons with existing protocol, we show that this protocol performs better than existing protocols in terms of average packet delivery overhead and packet generation.     

Workload management of cooperatively federated computing clusters

Cooperative resource sharing enables distinct organizations to form a federation of computing resources. The motivation behind cooperation is that organizations are likely to serve each other by trading unused CPU cycles given the existence of irregular usage patterns of their local resources. In this way, resource sharing would enable organizations to purchase resources at a feasible level while meeting peak computational throughput requirements. This federation results in community grid that must be managed. A functional broker is deployed to facilitate remote resource access within the community grid. A major issue is the problem of correlations in job arrivals caused by seasonal usage and/or coincident resource usage demand patterns. These correlations incur high levels of burstiness in job arrivals causing the job queue of the broker to grow to an extent such that its performance becomes severely impaired. Since job arrivals cannot be controlled, management strategies must be employed to admit jobs in a manner that can sustain a fair level of resource allocation performance at all participating organizations in the community. In this paper, we present a theoretical analysis of the problem of job traffic burstiness on resource allocation performance in order to elicit the general job management strategies to be employed. Based on the analysis, we define and justify a job management strategies for the resource broker to cope with overload conditions caused by job arrival correlations.