A METHOD FOR BALANCING HETEROGENEOUS REQUEST LOAD IN DHT-BASED P2P

Most P2P systems that provide a DHT abstraction distribute objects randomly among "peer nodes" in a way that results in some nodes having Θ(log N ) times as many objects as the average node. Further imbalance may result due to nonuniform distribution of objects in the identifier space and a high degree of heterogeneity in object loads and node capacities. Additionally, a node's load may vary greatly over time since the system can be expected to experience continuous insertions and deletions of objects, skewed object arrival patterns, and continuous arrival and departure of nodes.

The growing popularity of peer-to-peer (P2P) systems has necessitated the need for managing huge volumes of data efficiently to ensure acceptable user response times. Dynamically changing popularities of data items and skewed user query patterns in P2P systems may cause some of the peers to become bottlenecks, thereby resulting in severe load imbalance and consequently increased user response times. An effective load-balancing mechanism becomes a necessity in such cases. Such load-balancing can be achieved by efficient online data migration/replication. While much work has been done to harness the huge computing resources of P2P systems for high-performance computing and scientific applications, issues concerning load-balancing with a view towards faster access to data for normal users have not received adequate attention. Notably, the sheer size of P2P networks and the inherent dynamism of the environment pose significant challenges to load-balancing. The main contributions of our proposal are three-fold. First, we view a P2P system as comprising clusters of peers and present techniques for both intra-cluster and inter-cluster load-balancing. Second, we analyze the trade-offs between the options of migration and replication and formulate a strategy based on which the system decides at run-time which option to use. Third, we propose an effective strategy aimed towards automatic self-evolving clusters of peers. Our performance evaluation demonstrates that our proposed technique for inter-cluster load-balancing is indeed effective in improving the system performance significantly. To our knowledge, this work is one of the earliest attempts at addressing load-balancing via both online data migration and replication in P2P environments.

2006

Abstract Peer-Peer (P2P) technologies have recently been in the limelight for their disruptive power in particular they have emerged as a powerful multimedia content distribution mechanism. However, the widespread deployment of P2P networks are hindered by several issues, especially the ones that influence end-user satisfaction, including reliability. In this paper, we propose a solution for an efficient and user-oriented keyword lookup service on P2P networks.

Distributed Dynamic load balancing (DDLB) is an important system function destined to distribute workload among available processors to improve throughput and / or execution times of parallel computer . Instead of balancing the load in cluster by process migration or by moving an entire process to a less loaded computer, we make an attempt to balance load by splitting processes into separate jobs and then balance them to nodes. Many solutions have been proposed to tackle the load balancing issue in DHT-based P2P systems. However, all these solutions either ignore the heterogeneity nature of the system, or reassign loads among nodes without considering heterogeneity relationships, or both. In this paper, we present an efficient, Heterogeneity-aware load balancing scheme by using the concept of virtual servers. Proximity information is used to guide virtual server reassignments such that virtual servers are reassigned and transferred between physically close heavily loaded nodes and lightly loaded nodes, thereby minimizing the load movement cost and allowing load balancing to perform efficiently Keywords: Dynamic load balancing, Heterogeneity-aware, load balancing, peer-to-peer, virtual server

The growing popularity of peer-to-peer (P2P) systems has necessitated the need for managing huge volumes of data e#ciently to ensure acceptable user response times. Dynamically changing popularities of data items and skewed user query patterns in P2P systems may cause some of the peers to become bottlenecks, thereby resulting in severe load imbalance and consequently increased user response times. An e#ective load-balancing mechanism becomes a necessity in such cases. Such load-balancing can be achieved by e#cient online data migration/replication. While much work has been done to harness the huge computing resources of P2P systems for high-performance computing and scientific applications, issues concerning load-balancing with a view towards faster access to data for normal users have not received adequate attention. Notably, the sheer size of P2P networks and the inherent dynamism of the environment pose significant challenges to load-balancing. The main contributions of our propo...

Although a large number of users are using P2P systems, the ability of these systems to provide services with quality is questioned. A load balanced P2P system can provide services with smaller failure rate and better performance; hence, service quality of the system can be improved. Cluster systems have been adopted for services which are tolerant to faults. Although a cluster structure improving the reliability and robustness of a P2P system, the load unbalancing problem still remains because of the heterogeneities of nodes and requests. Existing dynamic load balancing mechanisms in P2P systems require extra connections and overhead on aggregating the load status from the nodes. We propose diffusive load balancing in a clustered P2P system, where a global balance is achieved through balancing the neighborhoods of all clusters within the existing overlay network. We simulated three load balancing schemes: directory-initiated, sender-initiated, and receiver-initiated; from an initially unbalanced situation, the results show that diffusive load balancing can achieve a global balance comparable to a centralized directory scheme, and the distributed directory-initiated scheme provides better results than the sender-or receiver-initiated schemes.

2011

Recently, many applications have used Peer-to-Peer (P2P) systems to overcome the current problems with client/server systems such as non-scalability, high bandwidth requirement and single point of failure. In this paper, we propose an efficient scheme to support efficient range query processing over structured P2P systems, while balancing both the storage load and access load. The paper proposes a rotating token scheme to balance the storage load by placing joining nodes in appropriate locations in the identifier space to share loads with already overloaded nodes. Then, to support range queries, we utilize an orderpreserving mapping function to map keys to nodes in order preserving way and without hashing. This may result in an access load imbalance due to non-uniform distribution of keys in the identifier space. Thus, we propose an adaptive replication scheme to relieve overloaded nodes by shedding some load on other nodes to balance the access load. We derive a formula for estimating the overhead of the proposed adaptive replication scheme. In this study, we carry simulation experiments with synthetic data to measure the performance of the proposed schemes. Our simulation experiments show significant gains in both storage load balancing and access load balancing.

Proceedings of 15th International Conference on Computer Communications and Networks, 2006

In the past few years, several DHT-based abstractions for peer-to-peer systems have been proposed. The main characteristic is to associate nodes (peers) with objects (keys) and to construct distributed routing structures to support efficient location. These approaches partially consider the load problem by balancing storage of objects without, however, considering lookup traffic. In this paper we present an analysis of structured peer-to-peer systems taking into consideration Zipf-like requests distribution. Based on our analysis, we propose a novel approach for load balancing taking into account object popularity. It is based on dynamic routing table reorganization in order to balance the routing load and on caching objects to balance the request load. We can therefore significantly improve the load balancing of traffic in these systems, and consequently their scalability and performance. Results from experimental evaluation demonstrate the effectiveness of our approach.

2007 IEEE 23rd International Conference on Data Engineering, 2007

We address the issue of measuring storage, or query load distribution fairness in peer-to-peer data management systems. Existing metrics may look promising from the point of view of specific peers, while in reality being far from optimal from a global perspective. Thus, first we define the requirements and study the appropriateness of various statistical metrics for measuring load distribution fairness towards these requirements. The metric proposed as most appropriate is the Gini coefficient (G). Second, we develop novel distributed sampling algorithms to compute G on-line, with high precision, efficiently, and scalably. Third, we show how G can readily be utilized on-line by higherlevel algorithms which can now know when to best intervene to correct load imbalances. Our analysis and experiments testify for the efficiency and accuracy of these algorithms, permitting the online use of a rich and reliable metric, conveying a global perspective of the distribution.

2008

Multimedia streaming of mostly user generated content is an ongoing trend, not only since the upcoming of Last.fm and YouTube. A distributed decentralized multimedia streaming architecture can spread the (traffic) costs to the user nodes, but requires to provide for load balancing and consider the heterogeneity of the participating nodes. We propose a DHT-based information gathering and analyzing architecture which controls the streaming request assignment in the system and thoroughly evaluate it in comparison to a distributed stateless strategy. We evaluated the impact of the key parameters in the allocation function which considers the capabilities of the nodes and their contribution to the system. Identifying the quality-bandwidth tradeoffs of the information gathering system, we show that with our proposed system a 53% better load balancing can be reached and the efficiency of the system is significantly improved.