Efficiency of tree-structured peer-to-peer service discovery systems

Abstract

The efficiency of service discovery is a crucial point in the development of fully decentralized middlewares intended to manage large scale computational grids. The work conducted on this issue led to the design of many peer-to-peer fashioned approaches. More specifically, the need for flexibility and complexity in the service discovery has seen the emergence of a new kind of overlays, based on tries, also known as lexicographic trees.Although these overlays are efficient and well designed, they require a costly maintenance and do not accurately take into account the heterogeneity of nodes and the changing popularity of the services requested by users.In this paper, we focus on reducing the cost of the maintenance of a particular architecture, based on a dynamic prefix tree, while enhancing it with some load balancing techniques that dynamically adapt the load of the nodes in order to maximize the throughput of the system. The algorithms developed couple a self-organizing prefix tree overlay with load balancing techniques inspired by similar previous works undertaken for distributed hash tables.After some simulation results showing how our load balancing heuristics perform in such an overlay and compare to other heuristics, we provide a fair comparison of this architecture and similar overlays recently proposed.

Optimization in a Self-stabilizing Service Discovery Framework for Large Scale Systems

“…An advantage of this technology is its ability to take into account the heterogeneity of the underlying physical network to build a more efficient tree overlay, as detailed in [13].…”

“…The Distributed Lexicographic Placement Table (DLPT [12,13]) is the hierarchical data structure that ensures request routing across overlay layer. DLPT belongs to the category of overlays that are distributed prefix trees, e.g., [4,23,1].…”

A practical study of self-stabilization for prefix-tree based overlay networks

“…If such a node does not exist, the query reaches the node with the label closest to this name, that triggers the creation of such a node. Tree nodes are dynamically, and in a decentralized way, distributed over the set of peers of the underlying network, as detailed in [5]. Service discovery queries are routed similarly.…”

“…DLPT adopts load balancing mechanisms that take into account the heterogeneity of the capacity of peers and the dynamic evolution of the popularity of services requested. These load balancing mechanisms used in DLPT were inspired by load balancing techniques used in DHTs, and have shown interesting performances in DLPT context [5]. …”

“…The Distributed Lexicographic Placement Table (DLPT) approach [4,6] is one of them, providing dynamic load balancing [5] and formal guarantees for fault tolerance [3], while most fault-tolerance for structured peer-to-peer networks rely on replication mechanisms, like [11]. Replication can be very costly in terms of computing and storage resources and does not ensure the recovery of the system after arbitrary transient failures (memory corruption, network disconnection, etc.).…”