Data load balancing is a challenging task in the P2P systems. Distributed hash table (DHT) abstraction, heterogeneous nodes, and non uniform distribution of objects are the reasons to cause load imbalance in structured P2P overlay networks. Previous works solved the load balancing problem by assuming the homogeneous capabilities of nodes, unawareness of the link latency during transferring load, and imposing logical structures to collect and reassign load. We propose a distributed load balancing algorithm with the topology awareness feature by using the concept of virtual servers. In our approach, each node collects neighborhood load information from physically close nodes and reassigns virtual servers to overlay nodes based upon the topology of underlying network. Consequently, our approach converges data load balancing quickly and it also reduces the load transfer cost between nodes. Moreover, our approach increases the quality of load balancing among close nodes of overlay and it also introduces a new tradeoff between the quality of load balancing and load transfer cost among all overlay nodes. Our simulations show that our approach reduces the load transfer cost and it saves network bandwidth respectively. Finally, we show that the in-degree imbalance of nodes, as a consequence of topology awareness, cannot lead to a remarkable problem in topology aware overlays.
Many load balancing methods have been suggested to handle this problem in P2P systems. The first work has been done by Chord @cite_16 . They diminish load of overlay nodes by using the concept of virtual servers. They allocate @math virtual servers per physical node and suppose that all overlay nodes are similar. However, their approach does not practically resolve the load balancing problem.
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Load balancing is a critical issue for the efficient operation of peer-to-peer networks. We give new protocols for several scenarios, whose provable performance guarantees are within a constant factor of optimal. First, we give an improved version of consistent hashing, a scheme used for item to node assignments in the Chord system. In its original form, it required every network node to operate O(log n) virtual nodes to achieve a balanced load, causing a corresponding increase in space and bandwidth usage. Our protocol eliminates the necessity of virtual nodes while maintaining a balanced load. Improving on related protocols, our scheme allows for the deletion of nodes and admits a simpler analysis, since the assignments do not depend on the history of the network. We then analyze several simple protocols for load sharing by movements of data from higher loaded to lower loaded nodes. These protocols can be extended to preserve the ordering of data items. As an application, we use the last protocol to give an efficient implementation of a distributed data structure for range searches on ordered data. IP anycast, with its innate ability to find nearby resources in a robust and efficient fashion, has long been considered an important means of service discovery. The growth of P2P applications presents appealing new uses for IP anycast. Unfortunately, IP anycast suffers from serious problems: it is very hard to deploy globally, it scales poorly by the number of anycast groups, and it lacks important features like load-balancing. As a result, its use is limited to a few critical infrastructure services such as DNS root servers. The primary contribution of this paper is a new IP anycast architecture, PIAS, that overcomes these problems while largely maintaining the strengths of IP anycast. PIAS makes use of a proxy overlay that advertises IP anycast addresses on behalf of group members and tunnels anycast packets to those members. The paper presents a detailed design of PIAS and evaluates its scalability and efficiency through simulation. We also present preliminary measurement results on anycasted DNS root servers that suggest that IP anycast provides good affinity. Finally, we describe how PIAS supports two important P2P and overlay applications. Current web server farms have simple resource allocation models. One model used is to dedicate a server or a group of servers for each customer. Another model partitions physical servers into logical servers and assigns one to each customer. Yet another model allows customers to be active on multiple servers using load-balancing techniques. The ability to handle peak loads while minimizing cost of resources required on the farm is a subject of ongoing research.We improve resource utilization through sharing. Customer load is expressed as a multidimensional probability distribution. Each customer is assigned to a server so as to minimize the total number of servers needed to host all the customers. We use the notion of complementarity of customers in simple heuristics for this stochastic vector-packing problem. The proposed method generates a resource allocation plan while guaranteeing a QoS to each customer. Simulation results justify our scheme. We present Araneola, a scalable reliable application-level multicast system for highly dynamic wide-area environments. Araneola supports multi-point to multi-point reliable communication in a fully distributed manner while incurring constant load on each node. For a tunable parameter k spl ges 3, Araneola constructs and dynamically maintains an overlay structure in which each node's degree is either k or k + 1, and roughly 90 of the nodes have degree k. Empirical evaluation shows that Araneola's overlay structure achieves three important mathematical properties of k-regular random graphs (i.e., random graphs in which each node has exactly k neighbors) with N nodes: (i) its diameter grows logarithmically with N; (ii) it is generally k-connected; and (iii) it remains highly connected following random removal of linear-size subsets of edges or nodes. The overlay is constructed at a very low cost: each join, leave, or failure is handled locally, and entails the sending of only about 3k messages in total. Given this overlay, Araneola disseminates multicast messages by gossiping over the overlay's links. We show that compared to a standard gossip-based multicast protocol, Araneola achieves substantial improvements in load, reliability, and latency. Finally, we present an extension to Araneola in which the basic overlay is enhanced with additional links chosen according to geographic proximity and available bandwidth. We show that this approach reduces the number of physical hops messages traverse without hurting the overlay's robustness.