The efficiency of greedy routing in hypercubes and butterflies

Includes bibliographical references (p. 24-26).Cover title. "October 1990".Research supported by the ARO. DAAL03-86-K-0171 Research supported by the NSF. ECS-8552419by George D. Stamoulis and John N. Tsitsiklis

Stable routing scheduling algorithms in multi-hop wireless networks

Stability is an important issue in order to characterize the performance of a network, and it has become a major topic of study in the last decade. Roughly speaking, a communication network system is said to be stableif the number of packets waiting to be delivered (backlog) is finitely bounded at any one time. In this paper we introduce a number of routing scheduling algorithms which, making use of certain knowledge about the network’s structure, guarantee stability for certain injection rates. First, we introduce two new families of combinatorial structures, which we call universally strong selectorsand generalized universally strong selectors, that are used to provide a set of transmission schedules. Making use of these structures, we propose two local-knowledgepacket-oblivious routing scheduling algorithms. The first proposed routing scheduling algorithm onlyneeds to know some upper bounds on the number of links and on the network’s degree, and is asymptotically optimal regarding the injection rate for which stability is guaranteed. The second proposed routing scheduling algorithm isclose to be asymptotically optimal, but it only needs to know an upper bound on the number of links. For such algorithms, we also provide some results regarding both the maximum latencies and queue lengths. Furthermore, we also evaluate how the lack of global knowledge about the system topology affects the performance of the routing scheduling algorithms.Funding for open access charge: CRUE-Universitat Jaume

Delivering Consistent Network Performance in Multi-tenant Data Centers

Data centers are growing rapidly in size and have recently begun acquiring a new role as cloud hosting platforms, allowing outside developers to deploy their own applications on large scales. As a result, today\u27s data centers are multi-tenant environments that host an increasingly diverse set of applications, many of which have very demanding networking requirements. This has prompted research into new data center architectures that offer increased capacity by using topologies that introduce multiple paths between servers. To achieve consistent network performance in these networks, traffic must be effectively load balanced among the available paths. In addition, some form of system-wide traffic regulation is necessary to provide performance guarantees to tenants. To address these issues, this thesis introduces several software-based mechanisms that were inspired by techniques used to regulate traffic in the interconnects of scalable Internet routers. In particular, we borrow two key concepts that serve as the basis for our approach. First, we investigate packet-level routing techniques that are similar to those used to balance load effectively in routers. This work is novel in the data center context because most existing approaches route traffic at the level of flows to prevent their packets from arriving out-of-order. We show that routing at the packet-level allows for far more efficient use of the network\u27s resources and we provide a novel resequencing scheme to deal with out-of-order arrivals. Secondly, we introduce distributed scheduling as a means to engineer traffic in data centers. In routers, distributed scheduling controls the rates between ports on different line cards enabling traffic to move efficiently through the interconnect. We apply the same basic idea to schedule rates between servers in the data center. We show that scheduling can prevent congestion from occurring and can be used as a flexible mechanism to support network performance guarantees for tenants. In contrast to previous work, which relied on centralized controllers to schedule traffic, our approach is fully distributed and we provide a novel distributed algorithm to control rates. In addition, we introduce an optimization problem called backlog scheduling to study scheduling strategies that facilitate more efficient application execution

Online Permutation Routing in Partitioned Optical Passive Star Networks

This paper establishes the state of the art in both deterministic and randomized online permutation routing in the POPS network. Indeed, we show that any permutation can be routed online on a POPS network either with $O(\frac{d}{g}\log g)$ deterministic slots, or, with high probability, with $5c\lceil d/g\rceil+o(d/g)+O(\log\log g)$ randomized slots, where constant $c=\exp (1+e^{-1})\approx 3.927$. When $d=\Theta(g)$, that we claim to be the "interesting" case, the randomized algorithm is exponentially faster than any other algorithm in the literature, both deterministic and randomized ones. This is true in practice as well. Indeed, experiments show that it outperforms its rivals even starting from as small a network as a POPS(2,2), and the gap grows exponentially with the size of the network. We can also show that, under proper hypothesis, no deterministic algorithm can asymptotically match its performance

Parallel computation on sparse networks of processors

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