206843939
The Quickest Path Problem in Distributed Computing Systems
Let N=(V, A, C, L) be an input network with node set V, arc set A, positive arc capacity function C, and nonnegative arc lead time function L. The quickest path problem is to find a path in N to transmit a given amount of data such that the transmission time is minimized. In this paper, distributed algorithms are developed for the quickest path problem in an asynchronous communication network. For the one-source quickest path problem, we present two algorithms that require O(rn2) messages, O(rn2) time, and O(rmn) messages, O(rn) time, respectively, where m=¦A¦, n=¦V ¦, and r is the number of distinct capacity values of N. For the all-pairs quickest path problem, we present an algorithm that requires O(mn) messages and O(m) time.
6244297
A layered communication system generator
Abstract Although many approaches have been proposed for modeling and automatically validating communication protocol entities, no approaches have been proposed for automatically implementing various layered communication systems. In the article, we propose a layered communication system generator that can automatically implement various layered communication systems. The layered communication system generator is established on the basis of a generalized communication system framework. In addition, a layered communicating finite state machine is introduced to specify the layered communication systems, and a matrix approach is proposed for protocol validation. We have implemented the proposed layered communication system generator in DOS and UNIX environments, in which several real-world protocols from Department of Defense and IEEE 802 standards organizations have been successfully developed.
17147705
Distributed algorithms for the quickest path problem
Let N = (V, A, C, L) be a network with node set V, arc set A, positive arc capacity function C, and nonnegative arc lead time function L. The quickest path problems is to find paths in N to transmit a given amount of data such that the transmission time is minimized. In this paper, distributed algorithms are developed for the quickest path problem in an asynchronous communication network. For the one-source quickest path problem, we present three algorithms that require O(rn2) messages and O(2) time, O(n) messages and O(rn) time, and O1+elog w) messages and O(rn1+elog w) time for any e, 0<e<1, respectively, where m = |A|, n = |V|, r is the number of distinct capacity values of N, and w is the maxima arc weight of N. For the all-pairs quickest path problem, we present an algorithm that requires O(mn) messages and O(m) time.
35779178
On the Quickest Path Problem
In this paper, we propose an O(mn2) time algorithm that finds all-pairs quickest paths in a given network N, where n and m are the numbers of nodes and arcs, respectively, in N. Besides, the quickest path between any two nodes can be determined in O(log m) time, provided O(mn2) time preprocessing is made.
30765152
On the Quickest Path Problem
Abstract Let N be an input network and σ be the amount of data to be transmitted. We present an O( mn 2 ) time algorithm that finds all-pairs quickest paths, for a given value of σ, and show that the quickest path between any two nodes for any value of σ can be found in O(log m ) time, provided O( mn 2 ) preprocessing time is spent.
40869256
Parallel algorithms for permutation graphs
In this paper, parallel algorithms are presented for solving some problems on permutation graphs. The coloring problem is solved inO(log2n) time usingO(n3/logn) processors on the CREW PRAM, orO(logn) time usingO(n3) processors on the CRCW PRAM. The weighted clique problem, the weighted independent set problem, the cliques cover problem, and the maximal layers problem are all solved with the same complexities. We can also show that the longest common subsequence problem belongs to the class NC.
1443282
Disk layout optimization for reducing energy consumption
Excessive power consumption is becoming a major barrier to extracting the maximum performance from high-performance parallel systems. Therefore, techniques oriented towards reducing power consumption of such systems are expected to become increasingly important in the future. Since disk systems of high-performance architectures are known to constitute a large fraction of the overall power budget, they form an important optimization target. Previous work on disk power management focuses primarily on hardware based schemes. However, since disk access pattern, i.e., the order in which disks on a system are accessed, is mainly shaped by the program code access pattern and disk layout of data, software techniques can also play a critical role in disk power management. Motivated by this observation, this paper proposes and evaluates a profile-driven disk layout optimization scheme for reducing energy consumption. The proposed scheme analyzes the array access traces obtained through profiling and determines, for each disk-resident data structure, the start disk from which the data is striped, the number of disks over which the data is striped, and the stripe unit. This paper discusses implementation details of our approach and presents an experimental evaluation of it. Our experiments with the entire suite of Spec95 floating-point benchmarks that are modified to operate on disk-resident data show that the proposed approach is very effective in reducing disk energy consumption. The results also show that the performance degradation caused by our approach is very small. This paper also compares our approach to a code restructuring based optimization mechanism and discusses how the two techniques can be combined for achieving the best results.
2371887
Locality-conscious process scheduling in embedded systems
In many embedded systems, the existence of a data cache might influence the effectiveness of process scheduling policy significantly. Consequently, a scheduling policy that takes inter-process data reuse into account might result in large performance benefits. In this paper, we focus on array-intensive embedded applications and present a locality-conscious scheduling strategy where we first evaluate the potential data reuse between processes, and then, using the results of this evaluation, select an order for process executions. We also show how process codes can be transformed by an optimizing compiler for increasing inter-process data reuse, thereby making locality-conscious scheduling more effective. Our experimental results obtained using two large, multi-process application codes indicate significant runtime benefits.
14724226
Adaptive Garbage Collection for Battery-Operated Environments
Energy is an important constraint for battery-operated embedded Java environments. In this work, we show how the garbage collector (GC) can be tuned to reduce the energy consumption of Java applications. In particular, we show the importance of tuning the frequency of invoking GC based on object allocation and garbage creation rates to optimize leakage energy consumption. We reduce the leakage energy by exploiting the supplygated leakage power optimization that is controlled by the GC. In this mechanism, power supply to memory banks that do not hold any useful data can be shut down. We implement a new adaptive GC mechanism within Sun’s KVM that optimizes the ability to shut down more banks. An evaluation of our approach using various embedded applications shows that the adaptive garbage collection scheme is effective in reducing the system energy consumption across different hardware configurations.
46218447
Parallelizing Progressive Computation for Skyline Queries in Multi-disk Environment
Given a set of d-dimensional points, skyline query returns the points that are not dominated by any other point on all dimensions. In this paper, we study an interesting scenario of skyline retrieval, where multi-dimensional points are distributed among multiple disks. Efficient algorithms for parallelizing progressive skyline computation are developed, using the parallel R-trees. The core of our scheme is to visit more entries from some disks simultaneously and enable effective pruning strategies with dominance checking to prune away the non-qualifying entries. Extensive experiments with synthetic data confirm that our proposed algorithms are both efficient and scalable.