23742969
High-performance message striping over reliable transport protocols
This paper introduces a high-performance middleware-level message striping approach to increase communication bandwidth for data transfer in heterogeneous clusters equipped with multiple networks. In this scheme, concurrency is used for the striping process. The proposed striping approach is designed to work at the middleware-level, between the distributed applications and the reliable transport protocols such as TCP. The middleware-level striping approach provides flexible, scalable, and hardware-, network-, and operating systems-independent communication bandwidth solution. In addition, techniques to enhance the performance of this approach over multiple networks are introduced. The proposed techniques, which minimize synchronization contention and eliminate the striping sequence header, rely on the features of a reliable transport protocol such as TCP to reduce some of the concurrent striping overhead. The techniques have been implemented and evaluated on a real cluster with multiple networks and the results show significant performance gains for data transfer over existing approaches.
11533778
Dynamic, reliability-driven scheduling of parallel real-time jobs in heterogeneous systems
In this paper, a heuristic dynamic scheduling scheme for parallel real-time jobs in a heterogeneous system is presented. The parallel real-time jobs studied in this paper are modelled by directed acyclic graphs (DAG). We assume a scheduling environment where parallel real-time jobs arrive at a heterogeneous system following a Poisson process. The scheduling algorithms developed in this paper take the reliability measure into account, in order to enhance the reliability of the heterogeneous system without any additional hardware cost. In addition, scheduling time and dispatch time are both incorporated into our scheduling scheme so as to make the scheduling result more realistic and precise. Admission control is in place so that a parallel real-time job whose deadline cannot be guaranteed is rejected by the system. The performance of the proposed scheme is evaluated via extensive simulations. The simulation results show that the heuristic algorithm performs significantly better than two other algorithms that do not consider reliability cost. Furthermore, results suggest that shortening the scheduling time results in a higher guarantee ratio. Hence, if parallel scheduling algorithm is devised and employed to shorten the scheduling time, the performance of the heterogeneous system will be further enhanced.
8918525
An efficient, low-cost inconsistency detection framework for data and service sharing in an Internet-scale system
In this paper, we argue that a broad range of Internet-scale distributed applications can benefit from an underlying low-cost consistency detection framework that is an alternative to inconsistency avoidance and can detect inconsistency among nodes sharing data or services in a timely manner. This paper first presents an overview of the inconsistency detection framework. Then, it discusses the detailed design of the two-layer inconsistency detection module, the core component of this framework, which can detect inconsistency among nodes in a timely manner. The proposed two-layer inconsistency detection module is evaluated both analytically and via simulations, which shows that this module can significantly reduce the time to detect inconsistency among nodes without adding much maintenance cost. Finally, this paper outlines the possible mechanisms to discern the application semantics and to resolve the detected inconsistencies
26735928
I/O Response Time in a Fault-Tolerant Parallel Virtual File System
A fault tolerant parallel virtual file system is designed and implemented to provide high I/O performance and high reliability. A queuing model is used to analyze in detail the average response time when multiple clients access the system. The results show that I/O response time is with a function of several operational parameters. It decreases with the increase in I/O buffer hit rate for read requests, write buffer size for write requests and number of server nodes in the parallel file system, while higher I/O requests arrival rate increases I/O response time.
10945986
Improving the performance of I/O-intensive applications on clusters of workstations
Load balancing in a workstation-based cluster system has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, if a significant portion of applications running in the system is I/O-intensive, traditional load balancing policies can cause system performance to decrease substantially. In this paper, two I/O-aware load-balancing schemes, referred to as IOCM and WAL-PM, are presented to improve the overall performance of a cluster system with a general and practical workload including I/O activities. The proposed schemes dynamically detect I/O load imbalance of nodes in a cluster, and determine whether to migrate some I/O load from overloaded nodes to other less- or under-loaded nodes. The current running jobs are eligible to be migrated in WAL-PM only if overall performance improves. Besides balancing I/O load, the scheme judiciously takes into account both CPU and memory load sharing in the system, thereby maintaining the same level of performance as existing schemes when I/O load is low or well balanced. Extensive trace-driven simulations for both synthetic and real I/O-intensive applications show that: (1) Compared with existing schemes that only consider CPU and memory, the proposed schemes improve the performance with respect to mean slowdown by up to a factor of 20; (2) When compared to the existing approaches that only consider I/O with non-preemptive job migrations, the proposed schemes achieve improvements in mean slowdown by up to a factor of 10; (3) Under CPU-memory intensive workloads, our scheme improves the performance over the existing approaches that only consider I/O by up to 47.5%.
1546029
Design and Analysis of Hierarchical Ring Networks for Shared-Memory Multiprocessors
ÐWe study four augmentations of ring networks which are intended to enhance a ring's efficiency as a communication medium significantly, while increasing its structural complexity only modestly. Chordal rings add ashortcuto edges, which can be viewed as chords, to the ring. Express rings are chordal rings whose chords are routed outside the ring. Multirings append subsidiary rings to edges of a ring and, recursively, to edges of appended subrings. Hierarchical ring networks (HRN's) append subsidiary rings to nodes of a ring and, recursively, to nodes of appended subrings. We show that these four modes of augmentation are very closely related: 1) Planar chordal rings, planar express rings, and multirings are topologically equivalent families of networks with the acutwidtho of an express ring translating into the atree deptho of its isomorphic multiring and vice versa. 2) Every depth-d HRN is a spanning subgraph of a depth-2dÿ 1 multiring. 3) Every depth-d multiring M can be embedded into a d-dimensional mesh with dilation 3 in such a way that some node of M resides at a corner of the mesh. 4) Every depth-d HRN H can be embedded into a d-dimensional mesh with dilation 2 in such a way that some node of H resides at a corner of the mesh. In addition to demonstrating that these four augmented ring networks are grid graphs, our embedding results afford us close bounds on how much decrease in diameter is achievable for a given increase in structural complexity for the networks. Specifically, we derive upper and lower bounds on the optimal diameters of N-node depth-d multirings and HRNs that are asymptotically tight for large N and d. Index TermsÐRing networks, chordal rings, express rings, multirings, hierarchical ring networks, grid graphs, graph embedding, diameter trade-offs.
16906364
Scalable and Robust Aggregation Techniques for Extracting Statistical Information in Sensor Networks
Wireless sensor networks have stringent constraints on system resources and data aggregation techniques are critically important. However, accurate data aggregation is difficult due to the variation of sensor readings and due to the frequent communication failures. To address these difficulties, we propose a scalable and robust data aggregation algorithm. The novelty of our work includes two aspects. First, our algorithm exploits the mixture model and the Expectation Maximization (EM) algorithm for parameter estimation. Hence, it captures the effects of aggregation over different scales while keeping the communication cost low. Second, our algorithm exploits loss-tolerant multi-path routing schemes. Hence, it obtains accurate statistical information even in the presence of high link and node failure rates. We demonstrate that our techniques reduce communication cost while retaining the precious statistical information otherwise neglected by other aggregation techniques. Our evaluation shows the proposed techniques are robust against link and node failures, and perform consistently well.
14525964
Adaptive strategies for efficiently locating internet-based servers in MANETs
Providing Internet access to Mobile Ad hoc Networks (MANETs) can greatly extend their applications, increase their scalability, and improve the quality of service. However, a critical problem is how the mobile hosts can locate Internet-based servers efficiently in a dynamic, unstructured network. Neither reactive strategies, where the hosts initiate on-demand server discovery, nor proactive strategies, where the servers periodically advertise their availability information, are optimal. To that end, this paper studies adaptive strategies that (1) combine both proactive advertising by the servers and on-demand discovery by the mobile hosts, and (2) determine the relative rate of proactive advertising and on-demand discovery adaptively according to the network characteristics including the host mobility level and the offered load. We propose and evaluate two novel, integrated algorithms. First, to determine the rate of proactive advertising, we propose an exponential backoff algorithm to probe the optimal operating point. Second, to reduce the network traffic due to reactive (on-demand) discovery, we propose a novel controlled flooding algorithm. Our simulation study reveals that, compared to the previous proactive strategies and reactive strategies, our adaptive strategies reduce network traffic for locating the servers by several times when the network has a moderate offered load and a low or high level of host mobility.
18773100
An Approach to Broaden the Semantic Coverage of ACL Speech Acts
Current speech-act based ACLs specify domain-independent information about communication and relegate domain-dependent information to an unspecified content language. This is reasonable, but the ACLs cover only a small fraction of the domain-independent information possible. As a key element of modern ACLs, the set of communicative acts needs to be as complete as possible to enable agents to communicate the widest range of information with agreed-upon semantics. This paper describes a new approach to broaden the semantic coverage of ACL speech acts. It provides agents with the ability to express more of the possible meanings in human languages and yields a more powerful ACL. Specifically, we first compare Austin's and Searle's classifications, and Ballmer and Brennenstuhl's comprehensive classification of speech acts. The main meaning categories and their semantics are given next. Finally, a multifaceted evaluation of our approach is presented, which points out that the approach potentially can combine the benefits of the FIPA ACL with Ballmer and Brennenstuhl's speech act classification, resulting in a more expressive ACL.
22852167
Parallel Random Tunneling Algorithm for Structural Optimization of Lennard-Jones Clusters up to N = 330
A random tunneling algorithm (RTA) is derived from the terminal repeller unconstrained subenergy tunneling (TRUST) algorithm, and the parallelization of the RTA is implemented with an island parallel paradigm. Combined with the techniques of angular moving, the parallel random tunneling algorithm (PRTA) is applied to the optimization of Lennard-Jones (LJ) atomic clusters, and all the global minima of LJ clusters with size up to 200 are successfully located. For the optimization of larger cluster, a PRTA with an improved seeding technique is developed and successfully applied to the optimization of LJ151-LJ309. Furthermore, the optimized structures of LJ309-330 with the PRTA, which have not been studied before, are also provided.
206799544
A continuation method for (strongly) monotone variational inequalities
We consider the variational inequality problem, denoted by VIP(X, F), whereF is a strongly monotone function and the convex setX is described by some inequality (and possibly equality) constraints. This problem is solved by a continuation (or interior-point) method, which solves a sequence of certain perturbed variational inequality problems. These perturbed problems depend on a parameterμ > 0. It is shown that the perturbed problems have a unique solution for all values ofμ > 0, and that any sequence generated by the continuation method converges to the unique solution of VIP(X,F) under a well-known linear independence constraint qualification (LICQ). We also discuss the extension of the continuation method to monotone variational inequalities and present some numerical results obtained with a suitable implementation of this method. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.