Non-contiguous Allocation Research Articles

Scalable Multiple Channel Scheduling with Optimal Utility in Wireless Local Area Networks

This paper studies scheduling algorithms for an infra-structure based wireless local area network with multiple simultaneous transmission channels. A reservation-based medium access control protocol is assumed where the base station (BS) allocates transmission slots to the system mobile stations based on their requests. Each station is assumed to have a tunable transmitter and tunable receiver. For this network architecture, the scheduling algorithms can be classified into two categories: contiguous and non-contiguous, depending on whether slots are allocated contiguously to the mobile stations. The main objective of the scheduling algorithms is to achieve high channel utility while having low time complexity. In this paper, we propose three scheduling algorithms termed contiguous sorted sequential allocation (CSSA), non-contiguous round robin allocation (NCRRA) and non-contiguous sorted round robin allocation (NCSRRA). Among these, CSSA schedules each station in contiguous mode, while other two algorithms, NCRRA and NCSRRA, schedule stations in non-contiguous mode. Through extensive analysis and simulation, the results demonstrate that the CSSA with only slightly increased complexity can achieve much higher channel utility when compared to the existing contiguous scheduling algorithms. The NCRRA and NCSRRA on the other hand, results in significantly lower complexity, while still achieving the optimal channel utility compared to existing non-contiguous scheduling algorithms.

Scheduling Precedence Constrained Parallel Tasks on Multiprocessors Using the Harmonic System Partitioning Scheme

We present an algorithm for scheduling precedence constrained parallel tasks on multiprocessors with noncontiguous processor allocation. The algorithm is called LLH(subscript m) (Level-by-level and List scheduling using the Harmonic system partitioning scheme), where m≥1 is a positive integer, which is a parameter for the harmonic system partitioning scheme. Three basic techniques are employed in algorithm LLH(subscript m). First, a task graph is divided into levels, and tasks are scheduled level by level to follow the precedence constraints. Second, tasks in the same level are scheduled using algorithm H(subscript m) developed in [16] for scheduling independent parallel tasks. The list scheduling method is used to implement algorithm H(subscript m). Third, the harmonic system partitioning scheme is used for processor allocation. It is shown here that for wide task graphs and some common task size distributions, as the size of a computation and m increase, and as the task sizes become smaller, the average-case performance ratio of algorithm LLH(subscript m) approaches one.

Scheduling algorithms for multiple channel wireless local area networks

This paper describes algorithms for scheduling traffic in wireless data networks with multiple channels per cell. The paper assumes that a reservation-based medium access control protocol is used. The main objective of the scheduling algorithms is to reduce the computation time while maximizing the utilization of the network resources, thereby improving the system throughput. The scheduling problem is presented as a variant of the bin-packing problem. In this paper, we consider two type of algorithms—contiguous and non-contiguous allocations. The algorithms are studied for wireless networks with single priority traffic and multiple priority traffic. A performance study that considers network utilization, computation time, and the throughput for 10 and 54 Mbps data-streams is presented. The results show that both the proposed algorithms perform better than MULTI-FIT in terms of overall throughput and computation time; and that the non-contiguous allocation performs better than the contiguous algorithm since the former results in smaller number of wasted slots.

Noncontiguous processor allocation algorithms for mesh-connected multicomputers

Current processor allocation techniques for highly parallel systems are typically restricted to contiguous allocation strategies for which performance suffers significantly due to the inherent problem of fragmentation. As a result, message-passing systems have yet to achieve the high utilization levels exhibited by traditional vector supercomputers. We are investigating processor allocation algorithms which lift the restriction on contiguity of processors in order to address the problem of fragmentation. Three noncontiguous processor allocation strategies-paging allocation, random allocation, and the Multiple Buddy Strategy (MBS)-are proposed and studied in this paper. Simulations compare the performance of the noncontiguous strategies with that of several well-known contiguous algorithms. We show that noncontiguous allocation algorithms perform better overall than the contiguous ones, even when message-passing contention is considered. We also present the results of experiments on an Intel Paragon XP/S-15 with 208 nodes that show noncontiguous allocation is feasible with current technologies.

Analysis of space allocation in a generally fragmented linear store

The space allocation process in a fragmented linear store with general fragmentation characteristics is analysed. For a given allocation requirement t, exact expression for the n-th moment of the allocation penalty for single block contiguous allocation is obtained, which for large t is shown to be O(¯F(t)−n), where ¯F(·) is the complementary distribution function of the free block sizes. For multiple block non-contiguous allocation, it is shown that the corresponding penalty can be approximated by an n-th degree polynomial and is O(tn) for large t. Compared with experimental values, the model results are able to achieve good agreement.

Analysis of Disc Fragmentation Using Markov Chains

The fragmented storage map is represented by a Markov model which incorporates correlation between locations not necessarily adjacent to one another. Formulae for the average access distance for contiguous and non-contiguous allocations are given. For large storage requirements, the performance penalty of the former can be substantially higher than that of the latter: they are shown to be O(kn) and O(n)respectively, where n is the storage requirement and k>1. The Markov model is also able to achieve close agreement with published measurements.

Analysis of Secondary Storage Fragmentation

Fragmentation of storage is a common phenomenon in both main storage and secondary storage. Fragmentation in secondary storage not only jeopardizes the allocation of space but also, since secondary storage access time–unlike that in main storage–is typically nonuniform, a decrease in efficiency arising from additional head movement may also result. A fragmented storage exhibits a checkerboard like pattern with free and occupied space alternating one another. Such alternating storage configuration is analyzed using alternating renewal processes. Two main types of storage processing are distinguished: contiguous storage allocation and noncontiguous storage allocation. The latter allows a request to be scattered over different locations while the former requires it to be allocated in a single continuous area. It is found that the reduction in operating efficiency due to fragmentation is quite substantial for both types of processing. The deterioration is especially marked in the former and is strongly affected by 1) the request size and 2) the storage utilization. Expressions for the generating functions of the performance penalties are derived. The results of the model are compared with published measurements and satisfactory agreement is obtained.