Spyros Voulgaris

CYCLON: Inexpensive Membership Management for Unstructured P2P Overlays

Unstructured overlays form an important class of peer-to-peer networks, notably when content-based searching is at stake. The construction of these overlays, which is essentially a membership management issue, is crucial. Ideally, the resulting overlays should have low diameter and be resilient to massive node failures, which are both characteristic properties of random graphs. In addition, they should be able to deal with a high node churn (i.e., expect high-frequency membership changes). Inexpensive membership management while retaining random-graph properties is therefore important. In this paper, we describe a novel gossip-based membership management protocol that meets these requirements. Our protocol is shown to construct graphs that have low diameter, low clustering, highly symmetric node degrees, and that are highly resilient to massive node failures. Moreover, we show that the protocol is highly reactive to restoring randomness when a large number of nodes fail.

Gossip-based peer sampling

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.

A robust and scalable peer-to-peer gossiping protocol

The newscast model is a general approach for communication in large agent-based distributed systems. The two basic services—membership management and information dissemination—are implemented by the same epidemic-style protocol. In this paper we present the newscast model and report on experiments using a Java implementation. The experiments involve communication in a large, wide-area cluster computer. By analysis of the outcome of the experiments we demonstrate that the system indeed shows the scalability and dependability properties predicted by our previous theoretical and simulation results.

Gossiping on MANETs: the beauty and the beast

Gossip protocols have emerged as a powerful technique for implementing highly scalable and robust services, such as information dissemination and aggregation. The fact that gossip protocols require very little or no structure to operate makes them particularly appealing to apply in dynamic systems, where topology changes are common (for instance, due to frequent faults or high churn rates). Therefore, gossip protocols seem particularly well fit to operate in wireless self-organizing networks. Unfortunately, these networks have a number of characteristics that impede the deployment of gossip protocols designed for wired networks. In this work we identify the inherent differences in communication between wired and wireless networks and their impact on the design and implementation of gossip protocols. In particular, our comparison includes drawing a distinction between the gossiping primitives suitable for each of these environments. In the context of this analysis, we conclude by presenting a list of open research questions.

An Epidemic Protocol for Managing Routing Tables in Very Large Peer-to-Peer Networks

Building self-maintained overlay networks for message routing has recently attracted significant research interest [5, 6, 7, 8, 9]. All suggested solutions have a common goal: To build and maintain structures (routing tables) that can be used to route messages. Several of the proposed algorithms focus on efficiency of bandwidth usage. However, their behavior is uncertain in the presence of highly dynamic environments, or serious disasters (i.e. half of the nodes crashing). In this paper we present an alternative approach to managing routing tables for peer-to-peer routing overlay networks, based on the Newscast epidemic protocol [1]. We substantiate our claims by presenting experimental results. We, therefore, demonstrate the potential of the Newscast epidemic protocol to create highly robust, self-administered overlay networks, able to sustain and adapt fast to severe network changes.

PolderCast: fast, robust, and scalable architecture for P2P topic-based pub/sub

We propose PolderCast, a P2P topic-based Pub/Sub system that is (a) fault-tolerant and robust, (b) scalable w.r.t the number of nodes interested in a topic and number of topics that nodes are interested in, and (c) fast in terms of dissemination latency while (d) attaining a low communication overhead. This combination of properties is provided by an implementation that blends deterministic propagation over maintained rings with probabilistic dissemination following a limited number of random shortcuts. The rings are constructed and maintained using gossiping techniques. The random shortcuts are provided by two distinct peer-sampling services: Cyclon generates purely random links while Vicinity produces interest-induced random links. We analyze PolderCast and survey it in the context of existing approaches. We evaluate PolderCast experimentally using real-world workloads from Twitter and Facebook traces. We use widely renowned Scribe [5] as a baseline in a number of experiments. Robustness with respect to node churn is evaluated through traces from the Skype superpeer network. We show that the experimental results corroborate all of the above properties in settings of up to 10K nodes, 10K topics, and 5K topics per-node.

Proactive Gossip-Based Management of Semantic Overlay Networks

Much research on content‐based P2P searching for file‐sharing applications has focused on exploiting semantic relations between peers to facilitate searching. Current methods suggest reactive ways to manage semantic relations: they rely on the usage of the underlying search mechanism, and infer semantic relationships based on the queries placed and the corresponding replies received. In this paper we follow a different approach, proposing a proactive method to build a semantic overlay. Our method is based on an epidemic protocol that clusters peers with similar content. Peer clustering is done in a completely implicit way, that is, without requiring the user to specify preferences or to characterize the content of files being shared. In our approach, each node maintains a small list of semantically optimal peers. Our simulation studies show that such a list is highly effective when searching files. The construction of this list through gossiping is efficient and robust, even in the presence of changes in the network. Copyright

Gossip-based clock synchronization for large decentralized systems

Numerous large-scale decentralized systems assume loosely synchronized clocks. Existing time protocols have not been designed for deployment in such systems, since they are complex and require manual configuration. We present the Gossiping Time Protocol (GTP), a completely self-managing epidemic time synchronization algorithm for peer-to-peer networks. In GTP, each node synchronizes its time by gossiping with other nodes. The decisions regarding sample evaluation and gossiping frequency are purely local, yet they result in consistent behavior of the whole system. Large-scale experimental evaluation of a 64,500-node network emulated on 65 machines indicates high scalability and reasonable accuracy of GTP.

AJIRA: A Lightweight Distributed Middleware for MapReduce and Stream Processing

Currently, MapReduce is the most popular programming model for large-scale data processing and this motivated the research community to improve its efficiency either with new extensions, algorithmic optimizations, or hardware. In this paper we address two main limitations of MapReduce: one relates to the models limited expressiveness, which prevents the implementation of complex programs that require multiple steps or iterations. The other relates to the efficiency of its most popular implementations (e.g., Hadoop), which provide good resource utilization only for massive volumes of input, operating sub optimally for smaller or rapidly changing input. To address these limitations, we present AJIRA, a new middleware designed for efficient and generic data processing. At a conceptual level, AJIRA replaces the traditional map/reduce primitives by generic operators that can be dynamically allocated, allowing the execution of more complex batch and stream processing jobs. At a more technical level, AJIRA adopts a distributed, multi-threaded architecture that strives at minimizing overhead for non-critical functionality. These characteristics allow AJIRA to be used as a single programming model for both batch and stream processing. To this end, we evaluated its performance against Hadoop, Spark, Esper, and Storm, which are state of the art systems for both batch and stream processing. Our evaluation shows that AJIRA is competitive in a wide range of scenarios both in terms of processing time and scalability, making it an ideal choice where flexibility, extensibility, and the processing of both large and dynamic data with a single programming model are either desirable or even mandatory requirements.

Brief announcement: performance analysis of cyclon, an inexpensive membership management for unstructured p2p overlays

Unstructured overlays form an important class of peer-to-peer networks, notably for content-based searching algorithms. Being able to build overlays with low diameter, that are resilient to unpredictable joins and leaves, in a totally distributed manner is a challenging task. Random graphs exhibit such properties, and have been extensively studied in literature. Cyclon algorithm is an inexpensive gossip-based membership management protocol described in detail in [1] that meets these requirements.