Efficient allocation of communication channels is critical for the performance of wireless mobile computing systems.The centralized channel allocation algorithms proposed in literature are neither robust, nor scalable.Distributed channel allocation schemes proposed in the past are complicated and require active participation of the mobile nodes.These algorithms are unable to dynamically adjust to spatial and temporal fluctuations in channel demand.We present a dynamic distributed channel allocation algorithm that can quickly adapt to changes in load distribution.The algorithm described in this paper requires minimal involvement of the mobile nodes, thus conserving their limited energy supply.The algorithm is proved to be deadlock free, starvation free and fair.It prevents co-channel interference and is scalable.

Abstract Two important components of a global scheduling algorithm are its transfer policy and its location policy. While the transfer policy determines whether a task should be transferred, the location policy determines where it should be transferred. Many global scheduling algorithms have been proposed to schedule tasks with deadline constraints. These algorithms try to transfer tasks only when task's deadlines cannot be met locally or local load is high (i.e. they take only corrective measures). However, a scheduling algorithm that takes preventive measures in addition to corrective measures can reduce potential deadline misses substantially. In this paper we present: (a) a load index which characterizes the system state and is more conducive to preventive and corrective measures; (b) a new transfer policy which takes preventive measures by doing anticipatory task transfers in addition to corrective measures. The proposed transfer policy adapts better to the workload by availing of the accurate system state made available by the proposed load index. An algorithm making use of the new transfer policy and the new load index is shown to reduce the number of deadline misses significantly when compared to algorithms taking only corrective measures.

The results of modeling the performance of searching large text databases (>10 gigabytes) via various parallel hardware architectures and search algorithms are discussed. The performance under load and the cost of each configuration are compared. Strengths, weaknesses, performance sensitivities, and search features supported for each configuration are also addressed. In addition, a common search workload used in the modeling is described. The search workload is derived from a set of searches run against the Chemical Abstracts (CA) file of bibliographic and abstract text available on STN International®. This common workload is applied to all configurations modeled to provide a common basis of comparison. © 1994 John Wiley & Sons, Inc.

Two important components of a global scheduling algorithm are its transfer policy and its location policy. While the transfer policy determines whether a task should be transferred, the location policy determines where it should be transferred. Based on their location policies, global scheduling algorithms can be broadly classified as receiver-initiated, sender-initiated, or symmetrically-initiated. The relative performance of these classes of algorithms has been shown to depend on the system workload. We present two adaptive location policies for global scheduling in distributed systems. These location policies are general, and can be used in conjunction with many existing transfer policies. By adapting to the system workload, the proposed policies capture the advantages of both sender-initiated and receiver-initiated policies. In addition, by adaptively directing their search activities toward the nodes that are most likely to be suitable counterparts in task transfers, the proposed policies provide short transfer latency and low overhead, and more important, high probability of finding a suitable counterpart if one exists. These properties allow these policies to deliver good performance over a very wide range of system operating conditions. The proposed policies are compared with nonadaptive policies, and are shown to considerably improve performance and to avoid causing system instability.>

The authors present a load index to characterize the system state that is more conducive to apply preventive and corrective measures, and a transfer policy which takes preventive measures by doing anticipatory task transfers in addition to corrective measures. Key features of this transfer policy are: (1) it is general and can be used in conjunction with a broad range of existing location policies, (2) it does not require the capability to transfer partially executed tasks, and (3) it adapts better to the system state by looking-ahead. A simulation study shows that an algorithm making use of the transfer policy and the load index reduces the number of deadline misses significantly when compared to algorithms taking only corrective measures.>

Two location policies that, by adapting to the system load, capture the advantages of receiver-initiated, sender-initiated, and symmetrically initiated algorithms are presented. A key feature of these location policies is that they are general and can be used in conjunction with a broad range of existing transfer policies. By means of simulation, two representative algorithms making use of these adaptive location policies are shown to be stable and to improve performance significantly relative to nonadaptive policies.>