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Distributed storage systems often employ erasure codes to achieve high data reliability while attaining space efficiency. Such storage systems are known to be susceptible to long tails in response time. It has been shown that in modern online applications such as Bing, Facebook, and Amazon, the long tail of latency is of particular concern, with 99.9th percentile response times that are orders of magnitude worse than the mean. Taming tail latency is very challenging in erasure-coded storage systems since quantify tail latency (i.e., xth-percentile latency for arbitrary x ∈ [0, 1]) has been a long-standing open problem. In this paper, we propose a mathematical model to quantify tail index of service latency for arbitrary erasure-coded storage systems, by characterizing the asymptotic behavior of latency distribution tails. When file size has a heavy tailed distribution, we find tail index, defined as the exponent at which latency tail probability diminishes to zero, in closed-form, and further show that a family of probabilistic scheduling algorithms are (asymptotically) optimal since they are able to achieve the exact tail index.

ISR develops, applies and teaches advanced methodologies of design and analysis toAbstract-Service discovery is an integral part of the ad hoc networking to achieve stand-alone and self-configurable communication networks. In this paper, we discuss possible service discovery architectures along with the required network support for their implementation, and we propose a distributed service discovery architecture which relies on a virtual backbone for locating and registering available services within a dynamic network topology. Our proposal consists of two independent components: (i) formation of a virtual backbone and (ii) distribution of service registrations, requests, and replies. The first component creates a mesh structure from a subset of a given network graph that includes the nodes acting as service brokers and a subset of paths (which we refer as virtual links) connecting them. Service broker nodes (SBNs) constitute a dominating set, i.e. all the nodes in the network are either in this set or only one-hop away from at least one member of the set. The second component establishes sub-trees rooted at service requesting nodes and registering servers for efficient dissemination of the service discovery probing messages. Extensive simulation results are provided for comparison of performance measures ,i.e. latency, success rate, and control message overhead, when different architectures and network support mechanisms are utilized in service discovery.

Our paper presents solutions using erasure coding, parallel connections to storage cloud and limited chunking (i.e., dividing the object into a few smaller segments) together to significantly improve the delay performance of uploading and downloading data in and out of cloud storage.TOFEC is a strategy that helps front-end proxy adapt to level of workload by treating scalable cloud storage (e.g. Amazon S3) as a shared resource requiring admission control. Under light workloads, TOFEC creates more smaller chunks and uses more parallel connections per file, minimizing service delay. Under heavy workloads, TOFEC automatically reduces the level of chunking (fewer chunks with increased size) and uses fewer parallel connections to reduce overhead, resulting in higher throughput and preventing queueing delay. Our trace-driven simulation results show that TOFEC's adaptation mechanism converges to an appropriate code that provides the optimal delay-throughput trade-off without reducing system capacity. Compared to a non-adaptive strategy optimized for throughput, TOFEC delivers 2.5× lower latency under light workloads; compared to a non-adaptive strategy optimized for latency, TOFEC can scale to support over 3× as many requests.

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Abstract-Efficient use of energy while providing an adequate level of connection to individual sessions is of paramount importance in multi-hop wireless networks. Energy efficiency and connection quality depend on mechanisms that span several communication layers due to the existing co-channel interference among competing flows that must reuse the limited radio spectrum. Although independent consideration of these layers simplifies the system design, it is often insufficient for wireless networks when the overall system performance is examined carefully. The multi-hop wireless extensions and the need for routing users' sessions from source to the destination only intensify this point of view. In this work, we present a framework for cross-layer design towards energy-efficient communication. Our approach is characterized by a synergy between the physical and the medium access control (MAC) layers with a view towards inclusion of higher layers as well. More specifically, we address the joint problem of power control and scheduling with the objective of minimizing the total transmit power subject to the end-to-end quality of service (QoS) guarantees for sessions in terms of their bandwidth and bit error rate guarantees. Bearing to the NP-hardness of this combinatorial optimization problem, we propose our heuristic solutions that follow greedy approaches.

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