Showing papers by "Li Zhang published in 2004"

Tycoon: an Implementation of a Distributed, Market-based Resource Allocation System

Abstract: Distributed clusters like the Grid and PlanetLab enable the same statistical multiplexing efficiency gains for computing as the Internet provides for networking. One major challenge is allocating resources in an economically efficient and low-latency way. A common solution is proportional share, where users each get resources in proportion to their pre-defined weight. However, this does not allow users to differentiate the value of their jobs. This leads to economic inefficiency. In contrast, systems that require reservations impose a high latency (typically minutes to hours) to acquire resources. We present Tycoon, a market based distributed resource allocation system based on proportional share. The key advantages of Tycoon are that it allows users to differentiate the value of their jobs, its resource acquisition latency is limited only by communication delays, and it imposes no manual bidding overhead on users. We present experimental results using a prototype implementation of our design.

Load balanced short path routing in wireless networks

Abstract: We study wireless network routing algorithms that use only short paths, for minimizing latency, and achieve good load balance, for balancing the energy use. We consider the special case when all the nodes are located in a narrow strip with width at most /spl radic/3/2 /spl ap/ 0.86 times the communication radius. We present algorithms that achieve good performance in terms of both measures simultaneously. In addition, our algorithms only use local information and can deal with dynamic change and mobility efficiently.

Ranking results for network search query

Abstract: A method and system for ranking results for a network search query. The method includes receiving a network search query; obtaining weblogs relevant to the search query from a database; scoring the weblogs based on a time when information pertaining to the search query appeared on weblogs; and displaying a ranking of the weblogs.

Fractionally cascaded information in a sensor network

Abstract: We address the problem of distributed information aggregation and storage in a sensor network, where queries can be injected anywhere in the network. The principle we propose is that a sensor should know a "fraction" of the information from distant parts of the network, in an exponentially decaying fashion by distance. We show how a sampled scalar field can be stored in this distributed fashion, with only a modest amount of additional storage and network traffic. Our storage scheme makes neighboring sensors have highly correlated world views; this allows smooth information gradients and enables local search algorithms to work well. We study in particular how this principle of fractionally cascaded information can be exploited to answer range queries about the sampled field efficiently. Using local decisions only we are able to route the query to exactly the portions of the field where the sought information is stored. We provide a rigorous theoretical analysis showing that our scheme is close to optimal.

Kinetic collision detection between two simple polygons

Abstract: We design a kinetic data structure for detecting collisions between two simple polygons in motion. In order to do so, we create a planar subdivision of the free space between the two polygons, called the external relative geodesic triangulation, which certifies their disjointness. We show how this subdivision can be maintained as a kinetic data structure when the polygons are moving, and analyze its performance in the kinetic setting.

Tradeoffs between stretch factor and load balancing ratio in routing on growth restricted graphs

Abstract: A graph has growth rate k if the number of nodes in any subgraph with diameter r is bounded by O(rk). The communication graphs of wireless networks and peer-to-peer networks often have small growth rate. In this paper we study the tradeoff between two quality measures for routing in growth restricted graphs. The two measures we consider are the stretch factor, which measures the lengths of the routing paths, and the load balancing ratio, which measures how evenly the traffic is distributed. We show that if the routing algorithm is required to use paths with stretch factor c, then its load balancing ratio is bounded by O((n/c)1-1/k), where k is the graph's growth rate. We illustrate our results by focusing on the unit disk graph for modeling wireless networks in which two nodes have direct communication if their distance is under certain threshold. We show that if the maximum density of the nodes is bounded by ρ, there exists routing scheme such that the stretch factor of routing paths is at most c, and the maximum load on the nodes is at most O(min(√ρn/c, n/c)) times the optimum. In addition, the bound on the load balancing ratio is tight in the worst case. As a special case, when the density is bounded by a constant, the shortest path routing has a load balancing ratio of O(√n). The result extends to k-dimensional unit ball graphs and graphs with growth rate k. We also discuss algorithmic issues for load balanced short path routing and for load balanced routing in spanner graphs.

Games and Queues

Abstract: We consider scheduling in distributed systems from a game theoretic point view while taking into account queuing theory methodologies. In this approach no one knows the global state of the system while users try to maximize their utility. Since the performance of such a blind scheduler is worse than the optimal, it induces users to employ strategies to improve their own utilization of the system. One such strategy is that of restarting a request if it is not satisfied in a given time. Since we assume users as non-cooperative and selfish, the problem is that of studying the characteristic of the Nash equilibrium in a large distributed system with no omniscient controls. We study the problem through computer experiments and analytical approaches. We obtain exact solutions in situations delimited by two extremes: one in which users never restart an initial request, and another one in which the user's requests are restarted infinitely often. Users can switch between these two behaviors. When the system load is below certain threshold, it is always better off to be impatient, and when the system load is higher than some threshold, it is always better to be patient. Between them there exists a homogeneous Nash equilibrium with non-trivial properties.