Practical load balancing for content requests in peer-to-peer networks

This paper studies the problem of balancing the demand for content in a peer-to-peer network across heterogeneous peer nodes that hold replicas of the content. Previous decentralized load balancing techniques in distributed systems base their decisions on periodic updates containing information about load or available capacity observed at the serving entities. We show that these techniques do not work well in the peer-to-peer context; either they do not address peer node heterogeneity, or they suffer from significant load oscillations which result in unutilized capacity. We propose a new decentralized algorithm, Max-Cap, based on the maximum inherent capacities of the replica nodes. We show that unlike previous algorithms, it is not tied to the timeliness or frequency of updates, and consequently requires significantly less update overhead. Yet, Max-Cap can handle the heterogeneity of a peer-to-peer environment without suffering from load oscillations. Mema Roussopoulos is an Assistant Professor of Computer Science on the Gordon McKay Endowment at Harvard University. Before joining Harvard, she was a Postdoctoral Fellow in the Computer Science Department at Stanford University. She received her PhD and Master’s degrees in Computer Science from Stanford, and her Bachelor’s degree in Computer Science from the University of Maryland at College Park. Her interests are in the areas of distributed systems, networking, and mobile and wireless computing. Mary Baker is a Senior Research Scientist at HP Labs. Her research interests include distributed systems, networks, mobile systems, security, and digital preservation. Before joining HP Labs she was on the faculty of the computer science department at Stanford University where she ran the MosquitoNet project. She received her PhD from the University of California at Berkeley.     

Adaptive processing of historical spatial range queries in peer-to-peer sensor networks

We investigate the problem of processing historical queries on a sensor network. Since data is considered to have been already collected at the sensor nodes, the main issue is exploring the spatial component of the query in order to minimize its cost represented by the energy consumption. We assume queries can be issued at any network node, i.e., there is no central base station and all nodes have only local knowledge of the network. On the one hand, a globally optimum query processing plan is desirable but its construction is not possible due to the lack of global knowledge of the network. On the other hand, while a simple network flooding is feasible, it is not a practical choice from a cost perspective. To address this problem we propose a two-phase query processing strategy, where in the first phase a path from the query originator to the query region is found and in the second phase the query is processed within the query region itself. This strategy is supported by analytical models that are used to dynamically select the best processing strategy depending on the query specifics. Our extensive analytical and experimental results show that our analytical models are accurate and that the two-phase strategy is better suited for small to medium sized queries, being up to 10 times more cost effective than a typical network flooding. In addition, the dynamic selection of a query processing technique proved itself capable of always delivering at least as good performance as the most energy efficient strategy for all query sizes. Research supported in part by NSERC Canada.     

Answering similarity queries in peer-to-peer networks

A variety of peer-to-peer (P2P) systems for sharing digital information are currently available and most of them perform searching by exact key matching. In this paper we focus on similarity searching and describe FuzzyPeer, a generic broadcast-based P2P system which supports a wide range of fuzzy queries. As a case study we present an image retrieval application implemented on top of FuzzyPeer. Users provide sample images whose sets of features are propagated through the peers. The answer consists of the top-k most similar images within the query horizon. In our system the participation of peers is ad hoc and dynamic, their functionality is symmetric and there is no centralized index.     

Building a network-aware and load-balanced peer-to-peer system for range queries

We present a structured P2P system called Donuts for range queries, which takes two important yet somewhat conflicting issues into account: proximity and load balance. Proximity allows physically close nodes to be arranged near each other in the overlay so as to reduce the cost of neighbor communications that occur quite often in a range-queriable system. Load balance is crucial because object distribution in a semantically meaningful key space is often skewed. Efficient load balance, however, requires flexible node position in the overlay, and thus conflicts with proximity.Donuts resolves the problem by separating physically close nodes into several overlay sections. By dynamically switching between these sections, they help one another balance their loads without altering overlay proximity too much. Still, breaking apart physically close nodes inevitably compromises overlay proximity. Therefore, we have put much effort in the overlay construction to ensure that load balance can be performed effectively and efficiently, with minimal damage to overlay proximity.     

Dynamic load balancing in IP-over-WDM optical burst switching networks

In this paper, we consider the problem of dynamic load balancing in wavelength division multiplexing (WDM)-based optical burst switching (OBS) networks. We propose a load balancing scheme based on adaptive alternate routing aimed at reducing burst loss. The key idea of adaptive alternate routing is to reduce network congestion by adaptively distributing the load between two pre-determined link-disjoint alternative paths based on the measurement of the impact of traffic load on each of them. We develop two alternative-path selection schemes to select link-disjoint alternative paths to be used by adaptive alternate routing. The path selection schemes differ in the way the cost of a path is defined and in the assumption made about the knowledge of the traffic demands. Through extensive simulation experiments for different traffic scenarios, we show that the proposed dynamic load balancing algorithm outperforms the shortest path routing and static alternate routing algorithms.     

A grid-based dynamic load balancing approach for data-centric storage in wireless sensor networks

In many data-centric storage techniques, each event corresponds to a hashing location by event type. However, most of them fail to deal with storage memory space due to high percentage of the load is assigned to a relatively small portion of the sensor nodes. Hence, these nodes may fail to deal with the storage of the sensor nodes effectively. To solve the problem, we propose a grid-based dynamic load balancing approach for data-centric storage in sensor networks that relies on two schemes: (1) a cover-up scheme to deal with a problem of a storage node whose memory space is depleted. This scheme can adjust the number of storage nodes dynamically; (2) the multi-threshold levels to achieve load balancing in each grid and all nodes get load balancing. Simulations have shown that our scheme can enhance the quality of data and avoid hotspot of the storage while there are a vast number of the events in a sensor network.     

一种动态的入侵检测系统负载均衡算法

目前的入侵检测不仅需要模式匹配,而且需要协议异常检测,提出了一种新动态的负载均衡算法,采用两层结构,对网络流量按照服务类型进行初步划分之后分别对每部分流量进行二次分配,并对每种类型的流量进行相应的协议异常检测。该算法能在不牺牲系统性能的前提下有效提高网络入侵检测系统的检测效率,降低误检率,并可有效地适应网络流量的变化,降低漏检率。     

Replica-aided load balancing in overlay networks

In recent years, there have been rapid advances in network infrastructure and technologies for end-user communication. However, because of network dynamics and resource limitation, providing scalable end-user communication services is challenging when the applications are utilized on a large-scale. To address this challenge, a replica-aided load balancing scheme (RALB) is proposed for enabling the nodes in an overlay networks to support the communication applications for a large number of users. This paper makes three unique contributions. First, we study the existing load balancing schemes and identify their weakness in handling time-varying workloads with frequent load fluctuations. Second, we introduce a sophisticated cost model for load balancing cost estimation, which captures the dependencies between the factors (e.g., the load, message number, and link latency). Third, we propose a performance tuning technique to minimize the load balancing cost. The extensive experiments show that RALB effectively reduces the load imbalance and eliminates the load balancing cost when compared to the existing load balancing schemes.     

Node and edge selectivity estimation for range queries in spatial networks

Modern applications requiring spatial network processing pose several interesting query optimization challenges. Spatial networks are usually represented as graphs, and therefore, queries involving a spatial network can be executed by using the corresponding graph representation. This means that the cost for executing a query is determined by graph properties such as the graph order and size (i.e., number of nodes and edges) and other graph parameters. In this paper, we present novel methods to estimate the number of nodes and edges in regions of interest in spatial networks, towards predicting the space and time requirements for range queries. The methods are evaluated by using real-life and synthetic data sets. Experimental results show that the number of nodes and edges can be estimated efficiently and accurately, with relatively small space requirements, thus providing useful information to the query optimizer.     

Dynamic load balancing for parallel polygon rendering

Using parallel processing for visualization speeds up computer graphics rendering of complex data sets. A parallel algorithm designed for polygon scan conversion and rendering is presented which supports fast rendering of highly complex data sets using advanced lighting models. Dedicated graphics rendering engines do not necessarily suit such data sets, although they can support real-time update of moderately complex scenes using simple lighting. Advantages to using a software-based approach include the feasibility of adding special rendering features to the program and the capability of integrating a parallel scientific application with a parallel graphics renderer. A new work decomposition strategy presented, called task adaptive, is based on dynamically partitioning the amount of computational work left at a given time. The algorithm uses a heuristic for dynamic task decomposition in which image space tasks are partitioned without requiring interruption of the partitioned processor. A sophisticated memory referencing strategy lets local memory access graphics data during rendering. This permits implementation of the algorithm on a distributed memory multiprocessor. An in-depth analysis of the overhead costs accompanying parallel processing shows where performance is adequate or could be improved     

Agent-based load balancing routing for LEO satellite networks

To ensure an intelligent engineering of traffic over entire satellite networks, a distributed routing scheme for low-earth orbit (LEO) satellite networks, agent-based load balancing routing (ALBR), is presented. Two kinds of agents are used. Mobile agents migrate autonomously to explore the path connecting source and destination, to gather inter-satellite link (ISL) cost, identifier and latitude of visited satellites. Meanwhile, stationary agents employ exponential forgetting function to estimate ISL queueing delay, calculate ISL cost using the sum of propagation and queueing delays; evaluate path cost considering satellite geographical position as well as ISL cost, finally update routing items. Through simulations on a Courier-like system, the proposed scheme is shown to achieve better load balancing, and can especially decrease packet loss ratio efficiently, guarantee better throughput and end-to-end delay bound in case of high traffic load. Furthermore, results from the implementation complexity analysis demonstrate that with the aid of agent technology, ALBR has lower on-board computation, storage, signaling requirements than other on-board routing schemes.     

Dynamic load balancing and efficient load estimators for asynchronous iterative algorithms

In a previous paper, we have shown the very high power of asynchronism for parallel iterative algorithms in a global context of grid computing. In this article, we study the interest of coupling load balancing with asynchronism in such algorithms. After proposing a noncentralized version of dynamic load balancing which is best suited to asynchronism, we verify its efficiency by some experiments on a general partial differential equation (PDE) problem. Finally, we give some general conditions for the use of load balancing to obtain good results with this kind of algorithm and discuss the choice of the residual as an efficient load estimator.     

Quantum load balancing in ad hoc networks

This paper presents a novel approach in targeting load balancing in ad hoc networks utilizing the properties of quantum game theory. This approach benefits from the instantaneous and information-less capability of entangled particles to synchronize the load balancing strategies in ad hoc networks. The quantum load balancing (QLB) algorithm proposed by this work is implemented on top of OLSR as the baseline routing protocol; its performance is analyzed against the baseline OLSR, and considerable gain is reported regarding some of the main QoS metrics such as delay and jitter. Furthermore, it is shown that QLB algorithm supports a solid stability gain in terms of throughput which stands a proof of concept for the load balancing properties of the proposed theory.     

眼科医疗影像文件存取下的HDFS负载均衡

在HDFS系统中,集群负载分配不均衡成为影响分布式文件存取速度的瓶颈。针对医院信息系统的负载现状,提出多属性双阈值决策的动态负载均衡算法,对分布式集群中使用HDFS默认的单属性评价、单阈值的负载均衡策略存在的缺陷加以改进。通过负载性能测试,对比证明运用多属性双阈值的负载均衡算法相比较HDFS默认的负载均衡更有利于将大量的影像负载数据相对均衡地分配到服务器集群中的各个节点上,大幅度地缩短了增加数据规模时数据服务器节点的平均响应时间,有利于提高HDFS集群整体的工作效率。     

Dynamic load balancing on Web-server systems

Popular Web sites cannot rely on a single powerful server nor on independent mirrored-servers to support the ever-increasing request load. Distributed Web server architectures that transparently schedule client requests offer a way to meet dynamic scalability and availability requirements. The authors review the state of the art in load balancing techniques on distributed Web-server systems, and analyze the efficiencies and limitations of the various approaches     

On scheduling data access with cooperative load balancing in vehicular ad hoc networks (VANETs)

For overcoming the vehicle to vehicle frequent disconnection problem in VANETs data dissemination, several approaches have been proposed, including the provision of Road Side Units (RSUs). Due to the short wireless transmission range of RSUs and vehicle mobility, a vehicle spends only a short period of time inside the range of an RSU. This limitation, together with possible overload of RSUs sited near busy road junctions, may mean that requests from vehicles are not served within the prescribed deadlines. In this paper, we propose a cooperative load balancing approach among RSUs, in which an RSU can transfer the overload requests to other RSUs. Load transfer is done based on a number of factors: request delay tolerance, current load of the transferee RSU, and the direction in which the vehicle is heading. Using a series of simulation experiments, we demonstrate that the proposed cooperative load balancing approach outperforms the non-cooperative (stand-alone) approaches in a wide range of scenarios based on our performance metrics.     

The load balancing problem in OTIS-Hypercube interconnection networks

An interconnection network architecture that promises to be an interesting option for future-generation parallel processing systems is the OTIS (Optical Transpose Interconnection System) optoelectronic architecture. Therefore, all performance improvement aspects of such a promising architecture need to be investigated; one of which is load balancing technique. This paper focuses on devising an efficient algorithm for load balancing on the promising OTIS-Hypercube interconnection networks. The proposed algorithm is called Clusters Dimension Exchange Method (CDEM). The analytical model and the experimental evaluation proved the excellence of OTIS-Hypercube compared to Hypercube in terms of various parameters, including execution time, load balancing accuracy, number of communication steps, and speed.

Contention-based performance evaluation of multidimensional range search in peer-to-peer networks

Performance evaluation of peer-to-peer search techniques has hitherto been based on simple performance metrics, such as message hop counts and total network traffic, mostly disregarding the inherently concurrent nature of peer-to-peer networks, where contention may arise. This paper is concerned with quantifying the effects of contention in P2P networks, focusing on networks for multidimensional range search. We evaluate peer-to-peer networks derived from recently proposed works, introducing two novel metrics related to concurrency and contention, namely responsiveness and throughput. Our results highlight the impact of contention on these networks, and demonstrate that some studied networks do not scale in the presence of contention. Also, our results indicate that certain P2P network properties believed to be desirable (e.g. even data distribution or uniform peer access) may not be as critical as previously believed.     

Fine grained load balancing in multi-hop wireless networks

In this paper we address the problem of local balancing in multi-hop wireless networks. We introduce the notion of proactive routing: after a short pre-processing phase in which nodes build their routing tables by exchanging messages with neighbors, we require that nodes decide the relay of each message without any further interaction with other nodes. Besides delivering very low communication overhead, proactive routing protocols are robust against some well known active attacks to network routing. In this framework, we develop a proactive routing protocol that is able to balance the local load. Experiments show that our protocol improves network lifetime up to 98% and that it delivers a network that is more robust against attacks that have the goal of getting control over a large part of the network traffic.