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Encoding examples: (a) CPU speeds from 1GHz to 3GHz are encoded into 4 intervals, each interval is mapped to a character 'a' through 'd', respectively; (b) Version numbers are similarly mapped into 6 intervals.
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Data sources, storage, computing resources and services are entities on Grids that require mechanisms for publication and lookup. A discovery service relies on efficient lookup to locate these objects from names or attributes. And on large-scale grids, these should be scalable and be able to support range queries and multi- criteria searching. Trie...
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... The core element of this architecture, indexing the services, is a distributed trie. It was called DLPT, for Distributed Lexicographic Placement Table or DPT for Dynamic Prefix Tree as referred to as in several papers [59] for instance. The DLPT is a stand alone system. ...
10 years. Ten years of research around high-performance computing in a distributed environment. And throughout these years, the development of the Diet middleware, increasing the value of that research. Today, a start-up company improves the status of Diet, giving it a new life. It feels only natural for me to give a complete review of this decade. The purpose of this document is to give a comprehensive description of the Diet middleware. Researches and developments carried out to create this Grid and Cloud middleware will be dis- cussed. Most of my researches focuses on Diet, hence the target of this document is twofold. First, to give an overview of my work and, secondly, to illustrate, through a real middleware, the issues met when designing, deploying and using this software platform dedicated to high-performance computing. Huge problems can now be computed over the Internet thanks to Grid Computing Environments or the new approach called Cloud Computing.
... These architectures usually support range queries, automatic completion of partial search strings and extend to multi-attribute queries. 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.). ...
... P-Grid builds a trie on the whole key-space, each leaf corresponding to a subset of the key-space. The Distributed Lexicographic Placement Table (DLPT) [4, 6] is based on a distributed prefix tree dynamically growing as services are declared by servers, as illustrated byFigure 1 giving an example of a tree growing with three services being sequentially declared: DGEMM, DTRSM and DTRMM from the BLAS library. The structure used is a particular prefix tree called Proper Greatest Common Prefix (PGCP) tree, defined as follows: A constant upper bound on both the degree of nodes and the depth of the tree can be assumed in such structures. ...
Service discovery is crucial in the development of fully decentralized computational grids. Among the significant amount of work produced by the convergence of peer-to-peer (P2P) systems and grids, a new kind of overlay networks, based on prefix trees, has emerged. In particular, the Distributed Lexicographic Placement Table (DLPT) approach is a decentralized and dynamic service discovery service. Fault-tolerance within the DLPT approach is achieved through best-effort policies relying on formal self-stabilization results. Self-stabilization means that the tree can become transiently inconsistent, but is guaranteed to autonomously converge to a correct topology after arbitrary crashes, in a finite time. However, during convergence, the tree may not be able to process queries correctly. In this paper, we present some simulation results having several objectives. First, we investigate the interest of self-stabilization for such architectures. Second, we explore, still based on simulation, a simple Time-To-Live policy to avoid useless processing during convergence time.
... The first contribution of this paper is the avoidance of the DHT: we developed a self-contained tree overlay able to both maintain the tree and map it onto the network. The load balancing issue has been mostly ignore by previous work on this architecture[5,6]. The second contribution is the design of a new load balancing heuristic based on the local maximization of the throughput. ...
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.
... The first contribution of this paper is the avoidance of the DHT: we developed a self-contained tree overlay able to both maintain the tree and map it onto the network. The load balancing issue has been mostly ignore by previous work on this architecture [5] [6]. The second contribution is the design of a new load balancing heuristic based on the local maximization of the throughput. ...
... The first contribution of this paper is the avoidance of the DHT: we developed a self-contained tree overlay able to both maintain the tree and map it onto the network. The load balancing issue has been mostly ignore by previous work on this architecture [5, 6]. The second contribution is the design of a new load balancing heuristic based on the local maximization of the throughput. ...
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.
Within distributed computing platforms, some computing abilities (or services) are offered to clients. To build dynamic applications using such services as basic blocks, a critical prerequisite is to discover those services. Traditional approaches to the service discovery problem have historically relied upon centralized solutions, unable to scale well in large unreliable platforms. In this chapter, we will first give an overview of the state of the art of service discovery solutions based on peer-to-peer (P2P) technologies that allow such a functionality to remain efficient at large scale. We then focus on one of these approaches: the Distributed Lexicographic Placement Table (DLPT) architecture, that provide particular mechanisms for load balancing and fault-tolerance. This solution centers around three key points. First, it calls upon an indexing system structured as a prefix tree, allowing multi-attribute range queries. Second, it allows the mapping of such structures onto heterogeneous and dynamic networks and proposes some load balancing heuristics for it. Third, as our target platform is dynamic and unreliable, we describe its powerful fault-tolerance mechanisms, based on self-stabilization. Finally, we present the software prototype of this architecture and its early experiments.
In the days of large scale, heterogeneous computing infrastructures gathering myriads of services, service discovery has become a critical feature that has to deal with the scale and dynamic nature of such platforms. The Spades project (Servicing Petascale Architectures and DistributEd System, 08-ANR-SEGI-025) is a consortium whose purpose is to promote new solutions to deal with a very large number of volatile and heterogeneous computing resources. For the aforementioned reasons, at the project’s core, the service discovery has been envisioned as fully decentralized. More precisely, the proposed P2P service discovery system proposed within the Spades project is based on the Dlpt approach (Distributed Lexicographic Placement Table) providing distributed structures and algorithms for such a feature. In this paper, an implementation of the Dlpt concepts into the middleware developed within the Spades project, called Sbam (Spades BAsed Middleware), is devised. Furthermore, its actual deployment over a nation-wide grid system, as well as its performance are detailed.
At times of large scale, heterogeneous computing infrastructures gathering myriads of services, service discovery has become a critical feature that has to deal with the scale and dynamic nature of such platforms. The SPADES project (Servicing Petascale Architectures and Distributed System) is a consortium whose purpose is to promote new solutions to deal with distributed, volatile and heterogeneous computing resources. For the aforementioned reasons, at the project's core, the service discovery has been envisioned as fully decentralized. More precisely, the proposed P2P service discovery system proposed within the SPADES project is based on the DLPT approach (Distributed Lexicographic Placement Table) providing distributed structures and algorithms for such a feature. In this paper, an implementation of the DLPT concepts into the middleware developed within the SPADES project, called SBAM, is devised. Moreover, its actual deployment over a nation-wide grid system, as well as its performance are detailed.
Loosely coupled applications can take advantage of the publish/subscribe communication paradigm. In this latter, subscribers declare which events, or which range of events, they wish to monitor, and are asynchronously informed whenever a publishers throws an event. In such a system, when a publication occurs, all peers whose subscriptions contain the publication must be informed. In our approach, the subscriptions are represented by a DR-tree, which is an R-tree where each minimum bounding rectangle is supervised by a peer. Instead of attempting to statically optimize the DR-tree, we give an on-line algorithm, the work function algorithm, which continually changes the DR-tree in response to the sequence of publications, in attempt to dynamically optimize the structure. The competitiveness of this algorithm is computed to be at most 5 for any example where there are at most three subscriptions and the R-tree has height 2. The benefit of the on-line approach is that no prior knowledge of the distribution of publications in the attribute space is needed.
