Resource management poses particular challenges in large-scale systems, such as server clusters that simultaneously process requests from a large number of clients. We mainly focus on the dynamic resource management in large scale cloud environment. Our core contribution centers around outlining a distributed middleware architecture and presenting one of its key elements, a gossip protocol P* that meets our 3 main design goals: (1) fairness of resource allocation with respect to hosted sites (2) efficient adaptation to load changes and (3) scalability in terms of both the number of machines and sites. We first present a protocol that maximizes the cloud utility under CPU and memory constraints and also minimizes the cost for adapting an allocation. Then, we extend that protocol to have a management control parameter, which can be done with the help of profiling technique. A particular challenge is to develop a gossip protocol that is robust against node failures. In this paper, we present P*, a gossip protocol for continuous monitoring of aggregates, which is robust against discontiguous failures (i.e., under the constraint that neighboring nodes do not fail within a short period of each other)
SASITHARAGAI, M.; PADMASHREE, A.; DHANALAKSHMI, T.; and GOWRI, S.
"DYNAMIC RESOURCE MANAGEMENT IN LARGE CLOUD ENVIRONMENTS USING DISTRIBUTED GOSSIP PROTOCOL,"
International Journal of Computer and Communication Technology: Vol. 7
, Article 15.
Available at: https://www.interscience.in/ijcct/vol7/iss4/15