generating rate, node throughput, and average packet latency indicate that the proposed ALB strategy is a much better alternative to a shortest-path routing on unbuffered tori. It achieves an almost optimal sustained packet generating rate, near-optimal latency, and acceptable node throughput. 1 Introduction

Computing shortest paths is a fundamental primitive for several social network applications including sociallysensitive ranking, location-aware search, social auctions and social network privacy. Since these applications compute paths in response to a user query, the goal is to minimize latency

-level eventdriven simulator, in which ROME protocols are implemented in detail, show that ROME protocols are efficient and scalable to metropolitan size. Furthermore, ROME protocols are highly resilient to network dynamics. The routing latency of ROME is only slightly higher than shortest-path latency

. Furthermore, ROME protocols are highly resilient to network dynamics. The routing latency of ROME is only slightly higher than shortest-path latency. To demonstrate scalability, we provide simulation performance results for ROME networks with up to 25,000 switches and 1.25 million hosts. I.

We consider the problem of answering point-to-point shortest path queries on massive social networks. The goal is to answer queries within tens of milliseconds while minimizing the memory requirements. We present a technique that achieves this goal for an extremely large fraction of path queries

for the asymmetric traveling salesman path problem [13, 5]. We prove an upper bound ρ = O ( √ n), which implies (for any fixed ɛ> 0) a polynomial time O(n 1/2+ɛ)approximation algorithm for directed latency. In the special case of metrics induced by shortest-paths in an unweighted directed graph, we give an O

This paper proposes a highly parallel and scalable reconfig-urable design for the All-Pairs Shortest-Paths (APSP) algo-rithm for very sparse networks. Our work is motivated by a computationally intensive bioinformatics application that employs this memory-latency bound algorithm. The pro

to the destination yields the shortest backup paths in the survived subgraph. However, it introduces significant increase of the routing table size, shedding light on the unbalanced trade-off between the length of the backup path and the routing table size.

) with X = fx 0 ; : : : ; xn g and Y = fy 0 ; : : : ; ymg, we wish to find the shortest path from x 0 to xn in G. This new problem requires\Omega\Gamma nm) time to solve in general, but we show that it can be solved in O(n+m log n) time if the weight matrices A and B of G are both concave, where for 0

of the MLAS problem. The optimal solution of small example networks sug-gests that an optimal scheduling can be neither shortest path nor dominating set based. Instead of yet another theoretical analysis with provable bounds, our work focuses on reducing the av-erage latency of general random topologies