Resource allocation in a cloud under virus attacks

Today’s large-scale services and applications use cloud computing to serve their users cost-effectively. As such, cloud based data centers form an attractive target for malicious entities who aim at attacking these services. We address the problem of how to manage one’s resources on a cloud environment as to provide the best service for its users while keeping it resilient to equipment failures due to attacks. The problem requires devising a resource placement mechanism that accounts for uncertainty both in the demand and the supply. We suggest a scheme for this problem and provide results on conditions under which this scheme is optimal. Particularly, we provide a set of attacks for which such efficient algorithms are guaranteed to find optimal allocation for any stochastic demand in which the conditions are satisfied. An attack is expressed by the supply distribution. We identify that the cumulative-cumulative distribution function plays a major role in the analysis. Moreover, we provide an alternative scheme for deriving an optimal allocation in the event that the conditions are not satisfied. Our analysis is relevant to many interesting problems of resource and inventory allocation and repositioning under uncertainty.