The Improvement of Chord Protocol about Structured P2P System

Chord protocol is one of the most classical protocols in structured P2P system, with the good effect, reliability, high query efficiency, and many other advantages. However, Chord agreement remains two main shortcomings the one that the searching speed of resources is slower, and the other that the detention of routing is higher. This paper in view of these shortcomings, combination with modification, then put forward the new Chord structure that super nodes and common nodes coexist, super nodes management general nodes. The new structure using Zipf-law determines the proportion of super nodes and ordinary nodes. The last, the new structure is simulated by simulation software, and the improved Chord protocol make better the previous shortcoming through the new structure compares with the Chord protocol

Using two-tier bitwise interest oriented QRP data structure for high clustering through interest similarity in SWB P2P systems

The concept of “Small-World” paradigm has been used by many peer-to-peer (P2P) systems to achieve high clustering and low number of hops to arrive to its desired target. This approach intends to improve performance of P2P systems. The Small world concept requires that the architecture of a P2P system to achieve high cluster coefficient and low average hop between any two randomly chosen peers. In this research, we propose an enhanced hierarchical overlay network by incorporating the concept of Small world into the base hierarchical architecture. This research adopts the Query Routing Protocol (QRP) data structure of a hierarchical P2P network by storing the interest information of files in the leaf peers in the network. The QRP in the leaf peers will be aggregated and propagated to the SuperPeer so that interest information could be used to form short-range, medium-range and long-range links with other SuperPeers to achieve low average hop. As peers join and leave the network, a proposed rewiring protocol is used to ensure peers are clustered by interest to form high clustering coefficient so that search activities are yielding higher relevance results in a more predictable fashion. We simulated the porposed small world P2P using test scenarios to evaluate recall rate of the small world P2P system. Our simulated results evaluate and benchmark our proposed Small-World Bee (SWB) overlay network with iCluster [3], Firework Query Model [5] and Limewire [1] to assess performance obtained and goals achieved in the research work so that future research directions could be planned

An Improved dynamic Load Balancing Algorithm applied to a Cafeteria System in a University Campus

Load-balancing algorithms play a key role in improving the performance of practical distributed systems that consist of heterogeneous nodes. The performance of any load-balancing algorithms and its convergence-rate is affected by the structural factors of the network that executes the algorithm. The performance deteriorated as the number of system nodes, the network-diameter, the communication-overhead increased. Moreover, additional technical-factors of the algorithm itself significantly affect the performance of rebalancing the load among nodes. Therefore, this paper proposes an approach that improves the performance of load-balancing algorithms by considering the load-balancing technical-factors and the structure of the network executes the algorithm. We applied the proposed method to a cafeteria system in a university campus and compared our approach with two significant methods presented in the literature. Results indicate that our approach considerably outperformed the original neighborhood approach and the nearest neighbor approach in terms of response time, throughput, communication overhead, and movements cost

Structured Overlay For Heterogeneous Environments: Design and Evaluation of Oscar

Recent years have seen advances in building large internet-scale index structures, generally known as structured overlays. Early structured overlays realized distributed hash tables (DHTs) which are ill suited for anything but exact queries. The need to support range queries necessitate systems which can handle uneven load distributions. However such systems suffer from practical problems - including poor latency, disproportionate bandwidth usage at participating peers or unrealistic assumptions on peers' homogeneity, in terms of available storage or bandwidth resources. In this paper we consider a system which is capable not only to support uneven load distributions but also to operate in heterogeneous environments, where each peer can autonomously decide how much of its resources to contribute to the system. We provide the theoretical foundations of realizing such a network and present a newly proposed system Oscar based on these principles. Oscar can construct efficient overlays given arbitrary load distributions by employing a novel scalable network sampling technique. The simulations of our system validate the theory and evaluate Oscar's performance under typical challenges encountered in real-life large-scale networked systems, including participant heterogeneity, faults and skewed and dynamic load-distributions. Thus the Oscar distributed index fills in an important gap in the family of structured overlays, bringing into life a practical internet-scale index, which can play a crucial role in enabling data-oriented applications distributed over wide-area networks

Dynamic data placement and discovery in wide-area networks

The workloads of online services and applications such as social networks, sensor data platforms and web search engines have become increasingly global and dynamic, setting new challenges to providing users with low latency access to data. To achieve this, these services typically leverage a multi-site wide-area networked infrastructure. Data access latency in such an infrastructure depends on the network paths between users and data, which is determined by the data placement and discovery strategies. Current strategies are static, which offer low latencies upon deployment but worse performance under a dynamic workload. We propose dynamic data placement and discovery strategies for wide-area networked infrastructures, which adapt to the data access workload. We achieve this with data activity correlation (DAC), an application-agnostic approach for determining the correlations between data items based on access pattern similarities. By dynamically clustering data according to DAC, network traffic in clusters is kept local. We utilise DAC as a key component in reducing access latencies for two application scenarios, emphasising different aspects of the problem: The first scenario assumes the fixed placement of data at sites, and thus focusses on data discovery. This is the case for a global sensor discovery platform, which aims to provide low latency discovery of sensor metadata. We present a self-organising hierarchical infrastructure consisting of multiple DAC clusters, maintained with an online and distributed split-and-merge algorithm. This reduces the number of sites visited, and thus latency, during discovery for a variety of workloads. The second scenario focusses on data placement. This is the case for global online services that leverage a multi-data centre deployment to provide users with low latency access to data. We present a geo-dynamic partitioning middleware, which maintains DAC clusters with an online elastic partition algorithm. It supports the geo-aware placement of partitions across data centres according to the workload. This provides globally distributed users with low latency access to data for static and dynamic workloads.Open Acces

Information Dissemination in Random Networks

Die vorliegende Dissertation beschÃ$ftigt sich mit der Dissemination von Information in einem Kommunikationsnetzwerk mit Broadcast-Kanal. Die zentrale Frage, welcher wir uns in dieser Arbeit widmen, ist wie man eine Nachricht ausgehend von einem Quellknoten effizient an alle anderen Knoten im Netzwerk verteilt. Hierbei verfolgen wir zwei Hauptziele: (1) Die Nachricht soll mit hoher Wahrscheinlichkeit alle Knoten im Netzwerk erreichen; (2) Es sollen so wenige Ébertragungen wie mÃglich stattfinden. In diesem Zusammenhang wenden wir uns hauptsÃ$chlich Algorithmen zur probabilistischen Dissemination von Information zu. Wir modellieren Kommunikationsnetzwerke als Zufallsgraphen, die auf stochastischen Prozessen beruhen. Wir verwenden Methoden der Graphentheorie sowie der stochastischen Geometrie um Disseminationsalgorithmen basierend sowohl auf Nachrichtenweiterleitung als auch auf Network Coding zu analysieren. Unser erstes Resultat ist eine analytische Studie von probabilistischem Flooding. In dieser Studie zeigen wir, wie die netzwerkweite Weiterleitungswahrscheinlichkeit gewÃ$hlt werden soll, sodass eine Nachricht mit hoher Wahrscheinlichkeit alle Knoten im Netzwerk erreicht. Als nÃ$chstes widmen wir uns der Frage, welche Vorteile ein probabilistischer Flooding-Algorithmus basierend auf Network Coding gegenÃber klassischen Methoden hat. Dabei wird die Network-Coding Methode mit dem weit verbreiteten MultiPoint Relay-Algorithmus verglichen. Der Vergleich erfolgt mittels analytischer und numerischer Methoden. Schlussendlich verwenden wir die Erkenntnisse der oben beschriebenen Studien dazu, um ein vernetztes Sensor-Aktuator-System zu entwerfen, welches als Notfallschutzsystem innerhalb von GebÃ$uden zum Einsatz kommen soll. Es soll Personen den kuerzesten sicheren Pfad zu den NotausgÃ$ngen anzeigen. Das Auffinden dieser Pfade erfolgt dabei verteilt basierend auf den Messungen der einzelnen Knoten, die Ãber das gesamte Netzwerk disseminiert werden.This dissertation focuses on the study of information dissemination in communication networks with a broadcast medium. The main problem we address is how to disseminate efficiently a message from a source node to all other network nodes. In terms of efficiency we target two goals: (1) to deliver a source message to all network nodes with high probability; and (2) to use as few transmissions as possible for a given target reachability. In this context, our main focus is devoted to probabilistic dissemination algorithms. Modeling networks as random graphs, which are built from stochastic processes, and using methods from graph theory and stochastic geometry we address both replication based and network coded information dissemination approaches. The first contribution is an analytical study of probabilistic flooding which answers the question of which is the minimum common network-wide forwarding probability each node should use such that a flooded message is obtained by all nodes with high probability. Next, we address the question of which benefits can be expected from network coded based probabilistic flooding. We compare these benefits with the ones from the well established replication based MultiPoint Relay flooding. The study of their efficiency is performed both by analytical techniques and numerical methods. Finally, we apply the insights gained from the study of information dissemination algorithms to the design of a sensor-actuator networked system for emergency response in indoor scenarios. The system guides people to the exits of a building via the shortest safe paths, computed autonomously by each node whenever a new measurement collected by a sensor is flooded throughout the network.Sérgio Armindo Lopes CrisóstomoAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in dt. und span. SpracheKlagenfurt, Alpen-Adria-Univ., Diss., 2012OeBB(VLID)241066