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271
Gossip-based Peer Sampling
, 2007
"... Gossip-based communication protocols are appealing in large-scale distributed applications such as information dissemination, aggregation, and overlay topology management. This paper factors out a fundamental mechanism at the heart of all these protocols: the peer-sampling service. In short, this se ..."
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Cited by 161 (43 self)
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Gossip-based communication protocols are appealing in large-scale distributed applications such as information dissemination, aggregation, and overlay topology management. This paper factors out a fundamental mechanism at the heart of all these protocols: the peer-sampling service. In short, this service provides every node with peers to gossip with. We promote this service to the level of a first-class abstraction of a large-scale distributed system, similar to a name service being a first-class abstraction of a local-area system. We present a generic framework to implement a peer-sampling service in a decentralized manner by constructing and maintaining dynamic unstructured overlays through gossiping membership information itself. Our framework generalizes existing approaches and makes it easy to discover new ones. We use this framework to empirically explore and compare several implementations of the peer-sampling service. Through extensive simulation experiments we show that—although all protocols provide a good quality uniform random stream of peers to each node locally—traditional theoretical assumptions about the randomness of the unstructured overlays as a whole do not hold in any of the instances. We also show that different design decisions result in severe differences from the point of view of two crucial aspects: load balancing and fault tolerance. Our simulations are validated by means of a wide-area implementation.
Programming pervasive and mobile computing applications with the tota middleware
- PerCom 2004. Proceedings of the Second IEEE Annual Conference on
, 2004
"... Pervasive and mobile computing call for suitable middleware and programming models to support the activities of complex software systems in dynamic network environments. In this paper we present TOTA (“Tuples On The Air”), a novel middleware and programming approach for supporting adaptive context-a ..."
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Cited by 123 (33 self)
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Pervasive and mobile computing call for suitable middleware and programming models to support the activities of complex software systems in dynamic network environments. In this paper we present TOTA (“Tuples On The Air”), a novel middleware and programming approach for supporting adaptive context-aware activities in pervasive and mobile computing scenarios. The key idea in TOTA is to rely on spatially distributed tuples, adaptively propagated across a network on the basis of application-specific rules, for both representing contextual information and supporting uncoupled interactions between application components. TOTA promotes a simple way of programming that facilitates access to distributed information, navigation in complex environments, and achievement of complex coordination tasks in a fully distributed and adaptive way, mostly freeing programmers and system managers form the need to take care of lowlevel issues related to network dynamics. This paper includes both application examples to clarify concepts and performance figures to show the feasibility of the approach.
PeerSim: A Scalable P2P Simulator ∗
"... The key features of peer-to-peer (P2P) systems are scalability and dynamism. The evaluation of a P2P protocol in realistic environments is very expensive and difficult to reproduce, so simulation is crucial in P2P research. ..."
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Cited by 98 (9 self)
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The key features of peer-to-peer (P2P) systems are scalability and dynamism. The evaluation of a P2P protocol in realistic environments is very expensive and difficult to reproduce, so simulation is crucial in P2P research.
Design patterns from biology for distributed computing
- ACM TRANS. AUTON. ADAPT. SYST
, 2006
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Gossiping in Distributed Systems
"... Gossip-based algorithms were first introduced for reliably disseminating data in large-scale distributed systems. However, their simplicity, robustness, and flexibility make them attractive for more than just pure data dissemination alone. In particular, gossiping has been applied to data aggregatio ..."
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Cited by 50 (0 self)
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Gossip-based algorithms were first introduced for reliably disseminating data in large-scale distributed systems. However, their simplicity, robustness, and flexibility make them attractive for more than just pure data dissemination alone. In particular, gossiping has been applied to data aggregation, overlay maintenance, and resource allocation. Gossiping applications more or less fit the same framework, with often subtle differences in algorithmic details determining divergent emergent behavior. This divergence is often difficult to understand, as formal models have yet to be developed that can capture the full design space of gossiping solutions. In this paper, we present a brief introduction to the field of gossiping in distributed systems, by providing a simple framework and using that framework to describe solutions for various application domains.
Ordered slicing of very large-scale overlay networks
- In Proceedings of the Sixth IEEE International Conference on Peer-to-Peer Computing (P2P 2006
, 2006
"... Recently there has been an increasing interest to harness the potential of P2P technology to design and build rich environments where services are provided and multiple applications can be supported in a flexible and dynamic manner. In such a context, resource assignment to services and applications ..."
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Cited by 42 (11 self)
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Recently there has been an increasing interest to harness the potential of P2P technology to design and build rich environments where services are provided and multiple applications can be supported in a flexible and dynamic manner. In such a context, resource assignment to services and applications is crucial. Current approaches require significant “manual-mode ” operations and/or rely on centralized servers to maintain resource availability. Such approaches are neither scalable nor robust enough. Our contribution towards the solution of this problem is proposing and evaluating a gossip-based protocol to automatically partition the available nodes into “slices”, also taking into account specific attributes of the nodes. These slices can be assigned to run services or applications in a fully selforganizing but controlled manner. The main advantages of the proposed protocol are extreme scalability and robustness. We present approximative theoretical models and extensive empirical analysis of the proposed protocol. 1.
Distributed slicing in dynamic systems
, 2006
"... Peer to peer (P2P) systems are moving from application specific architectures to a generic service oriented design philosophy. This raises interesting problems in connection with providing useful P2P middleware services capable of dealing with resource assignment and management in a large-scale, het ..."
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Cited by 30 (11 self)
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Peer to peer (P2P) systems are moving from application specific architectures to a generic service oriented design philosophy. This raises interesting problems in connection with providing useful P2P middleware services capable of dealing with resource assignment and management in a large-scale, heterogeneous and unreliable environment. The slicing service, has been proposed to allow for an automatic partitioning of P2P networks into groups (slices) that represent a controllable amount of some resource and that are also relatively homogeneous with respect to that resource. In this paper we propose two gossip-based algorithms to solve the distributed slicing problem. The first algorithm speeds up an existing algorithm sorting a set of uniform random numbers. The second algorithm statistically approximates the rank of nodes in the ordering. The scalability, efficiency and resilience to dynamics of both algorithms rely on their gossip-based models. These algorithms are proved viable theoretically and experimentally.
Robust monitoring of network-wide aggregates through gossiping
- In Proc. Tenth IFIP/IEEE International Symposium on Integrated Management (IM 2007
, 2007
"... Abstract — We examine the use of gossip protocols for continuous monitoring of network-wide aggregates. Aggregates are computed from local management variables using functions such as AVERAGE, MIN, MAX, or SUM. A particular challenge is to develop a gossip-based aggregation protocol that is robust a ..."
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Cited by 26 (6 self)
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Abstract — We examine the use of gossip protocols for continuous monitoring of network-wide aggregates. Aggregates are computed from local management variables using functions such as AVERAGE, MIN, MAX, or SUM. A particular challenge is to develop a gossip-based aggregation protocol that is robust against node failures. In this paper, we present G-GAP, a gossip protocol for continuous monitoring of aggregates, which is robust against discontiguous failures (i.e., under the constraint that neighboring nodes do not fail within a short period of each other). We formally prove this property, and we evaluate the protocol through simulation using real traces. The simulation results suggest that the design goals for this protocol have been met. For instance, the tradeoff between estimation accuracy and protocol overhead can be controlled, and a high estimation accuracy (below some 5 % error in our measurements) is achieved by the protocol, even for large networks and frequent node failures. Further, we perform a comparative assessment of G-GAP against a tree-based aggregation protocol using simulation. Surprisingly, we find that the tree-based aggregation protocol consistently outperforms the gossip protocol for comparative overhead, both in terms of accuracy and robustness.
Spatial Coordination of Pervasive Services through Chemical-inspired Tuple Spaces
"... To support and engineer the spatial coordination of distributed pervasive services, we propose a chemical-inspired model, which extends tuple spaces with the ability of evolving tuples mimicking chemical systems, i.e. in terms of reaction and diffusion rules that apply to tuples modulo semantic matc ..."
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Cited by 22 (12 self)
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To support and engineer the spatial coordination of distributed pervasive services, we propose a chemical-inspired model, which extends tuple spaces with the ability of evolving tuples mimicking chemical systems, i.e. in terms of reaction and diffusion rules that apply to tuples modulo semantic match. The suitability of this model is studied considering a self-adaptive display infrastructure providing nearby people with several visualisation services (advertisements, news, personal and social content). The key result of this paper is that general-purpose chemical reactions inspired by population dynamics can be used in pervasive applications to enact spatial computing patterns of competition and gradient-based interaction.
A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems
, 2006
"... In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. Much of the system’s functionality such as message routing, information retrieval and load sharing relies on modeling the global state. We refer to the ..."
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Cited by 20 (8 self)
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In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. Much of the system’s functionality such as message routing, information retrieval and load sharing relies on modeling the global state. We refer to the outcome of the function (e.g., the load experienced by each peer) as the model of the system. Since the state of the system is constantly changing, it is necessary to keep the models up-to-date. Computing global data mining models e.g. decision trees, k-means clustering in large distributed systems may be very costly due to the scale of the system and due to communication cost, which may be high. The cost further increases in a dynamic scenario when the data changes rapidly. In this paper we describe a two step approach for dealing with these costs. First, we describe a highly efficient local algorithm which can be used to monitor a wide class of data mining models. Then, we use this algorithm as a feedback loop for the monitoring of complex functions of the data such as its k-means clustering. The theoretical claims are corroborated with a thorough experimental analysis.
