VM multiplexing resource allocation scheme to manage decentralized resources

The design of our dynamic optimal proportional-share resource allocation method, which leverages the proportional share model.The key idea to redistribute available resources among running tasks dynamically, such that these tasks could use up the maximum capacity of each resource in a node (i.e., up to cðpsÞ), while each task’s execution time can be further minimized in a fair way. Cloud computing has emerged as a compelling paradigm for deploying distributed services. Resource allocation problem in cloud systems emphasizes how to harness the multiattribute resources by multiplexing operating systems. With virtual machine (VM) technology , we are able to multiplex several operating systems on the same hardware and allow task execution over its VM substrates without performance interference. Fine-grained resource sharing can be achieved as each VM substrate can be configured with proper shares of resources (such as CPU, memory, storage, network bandwidth) dynamically. These advanced techniques enable computing resources to be dynamically partitioned or reassembled to meet the elastic needs of end users. Such solutions create an unprecedented opportunity to maximize resource utilization, which were not possibly applied in most Grid systems that usually treat the underlying resources as indivisible ones and prevent simultaneous access to them. Today’s cloud architectures are not without problems. Most cloud services built on top of a centralized architecture may suffer denial-of-service (DoS) attacks, unexpected outages, and limited pooling of computational resources.