Grid environment consists of millions of dynamic and heterogeneous resources. A grid environment which deals with computing resources is computational grid and is meant for applications that involve larger computations. A scheduling algorithm is said to be efficient if and only if it performs better resource allocation even in case of resource failure. Allocation of resources is a tedious issue...

Since web workloads are known to vary dynamically with time, in this paper, we argue that dynamic resource allocation techniques are necessary to provide guarantees to web applications running on shared data centers. To address this issue, we use a system architecture that combines online measurements with prediction and resource allocation techniques. To perform resource allocation, we model a...

6.1 Introduction Wireless networks enable ubiquitous information and computational resource access , and become a popular networking solution. Recently, wireless mesh networks (WMN) [1, 2, 3, 4, 5, 6, 7] have attracted increasing attention and deployment as a high-performance and low-cost solution to last-mile broadband Internet access. In this chapter, we study the problem of resource allocati...

In large-scale grid systems, plenty of applications are constrained by soft or hard deadline requirement. However, it is difficult to guarantee the deadline requirements of these applications because of the dynamical nature of distributed systems. In this paper, a novel approach is proposed to evaluate the deadline-guarantee of co-allocation schemes that obtained from conventional co-allocation...

in this paper we consider the non-preemptive variant of a multi-mode resource constrained project scheduling problem (mrcpsp) with mode identity, in which a set of project activities is partitioned into disjoint subsets while all activities forming one subset have to be processed in the same mode. we present a depth-first branch and bound algorithm for the resource constrained project schedulin...

The constrained multiagent task scheduling problem is a problem class that describes complex scheduling problems that integrate stochastic task allocation with constraint satisfaction for agents that concurrently execute multiple tasks. The combination of elements from constraint satisfaction, task allocation and resource scheduling produces a challenging class of problems. Unfortunately, exist...

In order to improve the bandwidth allocation considering feedback of operational environment, adaptable bandwidth planning based on reinforcement learning is proposed. The approach is based on new constrained scheduling algorithms controlled by reinforcement learning techniques. Different constrained scheduling algorithms,, such as “conflict free scheduling with minimum duration”, “partial disp...