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.

Recent developments in information technology have brought about important changes in distributed computing. New environments have emerged such as massively large-scale wide area computer networks and mobile ad hoc networks. These new environments are extremely dynamic, unreliable and often large-scale. Traditional approaches to designing distributed applications based on central control, small scale or strict reliability assumptions are not suitable for exploiting the enormous potential of these environments. Based on the observation that living organisms efficiently organize a large number of unreliable and dynamically changing components (cells, molecules, individuals of a population, etc) it has long been an interesting area of research to try to figure out what are the key ideas that make biological systems work and to apply these ideas in distributed systems engineering. In this paper we propose a conceptual framework that captures a few basic biological processes such as plain diffusion, reaction-diffusion, proliferation, etc. We show through examples how to implement practically relevant functions based on these ideas. Using a common evaluation methodology, we show that these applications have state-of-the-art effectivity and performance while they inherit some nice properties of biological systems, such as adaptivity and robustness to failure.

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.

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.

Peer-to-Peer (P2P) search requires intelligent decisions for query routing: selecting the best peers to which a given query, initiated at some peer, should be forwarded for retrieving additional search results. These decisions are based on statistical summaries for each peer, which are usually organized on a per-keyword basis and managed in a distributed directory of routing indices. Such architectures disregard the

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.

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.

Abstract — The concept of superpeer has been introduced to improve the performance of popular P2P applications. A superpeer is a “powerful ” node that acts as a server for a set of clients, and as an equal with respect to other superpeers. By exploiting heterogeneity, the superpeer paradigm can lead to improved efficiency, without compromising the decentralized nature of P2P networks. The main issues in constructing superpeer-based overlays are the selection of superpeers and the association between superpeers and clients. Generally, superpeers are either run voluntarily (without an explicit selection process), or chosen among the “best ” nodes in the network, for example those with the most abundant resources, such as bandwidth or storage. In several contexts, however, shared resources are not the only factor; latency between clients and superpeers may play an important role, for example in online games and IP-Telephony applications. This paper presents SG-2, a novel protocol for building and maintaining proximity-aware superpeer topologies. SG-2 uses a gossip-based protocol to spread messages to nearby nodes and a biology-inspired task allocation mechanism to promote the “best ” nodes to superpeer status. The paper includes extensive simulation experiments to prove the efficiency, scalability and robustness of SG-2. Index Terms — P2P, superpeer, overlay, latency, quality of service.

In recent years the labels “gossip ” and “gossip-based ” have been applied to an increasingly general class of algorithms, including approaches to information aggregation, overlay network management and clock synchronization. These algorithms are intuitively similar, irrespective of their purpose. Their distinctive features include relying on local information, being round-based and relatively simple, and having a bounded information transmission and processing complexity in each round. Our position is that this class can and should be significantly extended to involve algorithms from other disciplines that share the same orsimilar distinctive features, like certain parallel numerical algorithms, routing protocols, bio-inspired algorithms and cellular automata, to name but a few. Such a broader perspective would allow us to import knowledge and tools to design and understand gossip-based distributed systems, and we could also export accumulated knowledge to re-interpret some of the problems in other disciplines, such as vehicular traffic control. In this position paper we describe a number of areas that show parallels with gossip protocols. These example areas will hopefully serve as inspiration for future research. In addition, we believe that comparisons with other fields also helps clarify the definition of gossip protocols and represents a necessary first step towards an eventual formal definition. 1.

Information retrieval (IR) in peer-to-peer (P2P) networks, where the corpus is spread across many loosely coupled peers, has recently gained importance. In contrast to IR systems on a centralized server or server farm, P2P IR faces the additional challenge of either being oblivious to global corpus statistics or having to compute the global measures from local statistics at the individual peers in an efficient, distributed manner. One specific measure of interest is the global document frequency for different terms, which would be very beneficial as term-specific weights in the scoring and ranking of merged search results that have been obtained from different peers. This paper presents an efficient solution for the problem of estimating global document frequencies in a large-scale P2P network with very high dynamics where peers can join and leave the network on short notice. In particular, the developed method takes into account the fact that the local document collections of autonomous peers may arbitrarily overlap, so that global counting needs to be duplicateinsensitive. The method is based on hash sketches as a technique for compact data synopses. Experimental studies demonstrate the estimator’s accuracy, scalability, and ability to cope with high dynamics. Moreover, the benefit for ranking P2P search results is shown by experiments with real-world Web data and queries. 1.