2 resultados para Availability Heuristic

em Boston University Digital Common


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Reliability and availability have long been considered twin system properties that could be enhanced by distribution. Paradoxically, the traditional definitions of these properties do not recognize the positive impact of recovery as distinct from simple repair and restart on reliability, nor the negative effect of recovery, and of internetworking of clients and servers, on availability. As a result of employing the standard definitions, reliability would tend to be underestimated, and availability overestimated. We offer revised definitions of these two critical metrics, which we call service reliability and service availability, that improve the match between their formal expression, and intuitive meaning. A fortuitous advantage of our approach is that the product of our two metrics yields a highly meaningful figure of merit for the overall dependability of a system. But techniques that enhance system dependability exact a performance cost, so we conclude with a cohesive definition of performability that rewards the system for performance that is delivered to its client applications, after discounting the following consequences of failure: service denial and interruption, lost work, and recovery cost.

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The objective of unicast routing is to find a path from a source to a destination. Conventional routing has been used mainly to provide connectivity. It lacks the ability to provide any kind of service guarantees and smart usage of network resources. Improving performance is possible by being aware of both traffic characteristics and current available resources. This paper surveys a range of routing solutions, which can be categorized depending on the degree of the awareness of the algorithm: (1) QoS/Constraint-based routing solutions are aware of traffic requirements of individual connection requests; (2) Traffic-aware routing solutions assume knowledge of the location of communicating ingress-egress pairs and possibly the traffic demands among them; (3) Routing solutions that are both QoS-aware as (1) and traffic-aware as (2); (4) Best-effort solutions are oblivious to both traffic and QoS requirements, but are adaptive only to current resource availability. The best performance can be achieved by having all possible knowledge so that while finding a path for an individual flow, one can make a smart choice among feasible paths to increase the chances of supporting future requests. However, this usually comes at the cost of increased complexity and decreased scalability. In this paper, we discuss such cost-performance tradeoffs by surveying proposed heuristic solutions and hybrid approaches.