We propose a simple distributed hash table called ReCord, which is a generalized version of Randomized-Chord and offers improved tradeoffs in performance and topology maintenance over existing P2P systems. ReCord is scalable and can be easily implemented as an overlay network, and offers a good tradeoff between the node degree and query latency. For instance, an @math -node ReCord with @math node degree has an expected latency of @math hops. Alternatively, it can also offer @math hops latency at a higher cost of @math node degree. Meanwhile, simulations of the dynamic behaviors of ReCord are studied.
It is difficult to say which one of above proposed DHTs is best". Each routing algorithm offers some insight on routing in overlay network. One appropriate strategy is to combine these insights and formulate an even better scheme @cite_0 .
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The various proposed DHT routing algorithms embody several different underlying routing geometries. These geometries include hypercubes, rings, tree-like structures, and butterfly networks. In this paper we focus on how these basic geometric approaches affect the resilience and proximity properties of DHTs. One factor that distinguishes these geometries is the degree of flexibility they provide in the selection of neighbors and routes. Flexibility is an important factor in achieving good static resilience and effective proximity neighbor and route selection. Our basic finding is that, despite our initial preference for more complex geometries, the ring geometry allows the greatest flexibility, and hence achieves the best resilience and proximity performance. Distributed Hash Tables (DHTs) are very efficient distributed systems for routing, but at the same time vulnerable to disruptive nodes. Designers of such systems want them used in open networks, where an adversary can perform a sybil attack by introducing a large number of corrupt nodes in the network, considerably degrading its performance. We introduce a routing strategy that alleviates some of the effects of such an attack by making sure that lookups are performed using a diverse set of nodes. This ensures that at least some of the nodes queried are good, and hence the search makes forward progress. This strategy makes use of latent social information present in the introduction graph of the network. A number of distributed hash table (DHT)-based protocols have been proposed to address the issue of scalability in peer-to-peer networks. In this paper, we present Ulysses, a peer-to-peer network based on the butterfly topology that achieves the theoretical lower bound of log n log log n on network diameter when the average routing table size at nodes is no more than log n. Compared to existing DHT-based schemes with similar routing table size, Ulysses reduces the network diameter by a factor of log log n, which is 2–4 for typical configurations. This translates into the same amount of reduction on query latency and average traffic per link node. In addition, Ulysses maintains the same level of robustness in terms of routing in the face of faults and recovering from graceful ungraceful joins and departures, as provided by existing DHT-based schemes. The performance of the protocol has been evaluated using both analysis and simulation. Copyright © 2004 AEI Distributed hash table (DHT) systems are an important class of peer-to-peer routing infrastructures. They enable scalable wide-area storage and retrieval of information, and will support the rapid development of a wide variety of Internet-scale applications ranging from naming systems and file systems to application-layer multicast. DHT systems essentially build an overlay network, but a path on the overlay between any two nodes can be significantly different from the unicast path between those two nodes on the underlying network. As such, the lookup latency in these systems can be quite high and can adversely impact the performance of applications built on top of such systems.In this paper, we discuss a random sampling technique that incrementally improves lookup latency in DHT systems. Our sampling can be implemented using information gleaned from lookups traversing the overlay network. For this reason, we call our approach lookup-parasitic random sampling (LPRS). LPRS is fast, incurs little network overhead, and requires relatively few modifications to existing DHT systems.For idealized versions of DHT systems like Chord, Tapestry and Pastry, we analytically prove that LPRS can result in lookup latencies proportional to the average unicast latency of the network, provided the underlying physical topology has a power-law latency expansion. We then validate this analysis by implementing LPRS in the Chord simulator. Our simulations reveal that LPRS-Chord exhibits a qualitatively better latency scaling behavior relative to unmodified Chord.Finally, we provide evidence which suggests that the Internet router-level topology resembles power-law latency expansion. This finding implies that LPRS has significant practical applicability as a general latency reduction technique for many DHT systems. This finding is also of independent interest since it might inform the design of latency-sensitive topology models for the Internet. During recent years, Distributed Hash Tables (DHTs) have been extensively studied through simulation and analysis. However, due to their limited deployment, it has not been possible to observe the behavior of a widely-deployed DHT in practice. Recently, the popular eMule file-sharing software incorporated a Kademlia-based DHT, called Kad, which currently has around one million simultaneous users. In this paper, we empirically study the performance of the key DHT operation, lookup, over Kad. First, we analytically derive the benefits of different ways to increase the richness of routing tables in Kademlia-based DHTs. Second, we empirically characterize two aspects of the accuracy of routing tables in Kad, namely completeness and freshness, and characterize their impact on Kad’s lookup performance. Finally, we investigate how the efficiency and consistency of lookup in Kad can be improved by performing parallel lookup and maintaining multiple replicas, respectively. Our results pinpoint the best operating point for the degree of lookup parallelism and the degree of replication for Kad. We study a fundamental tradeoff issue in designing a distributed hash table (DHT) in peer-to-peer (P2P) networks: the size of the routing table versus the network diameter. Observing that existing DHT schemes have either 1) a routing table size and network diameter both of O(log sub 2 n), or 2) a routing table of size d and network diameter of O(n sup 1 d ), S. (2001) asked whether this represents the best asymptotic "state-efficiency" tradeoffs. We show that some straightforward routing algorithms achieve better asymptotic tradeoffs. However, such algorithms all cause severe congestion on certain network nodes, which is undesirable in a P2P network. We rigorously define the notion of "congestion" and conjecture that the above tradeoffs are asymptotically optimal for a congestion-free network. The answer to this conjecture is negative in the strict sense. However, it becomes positive if the routing algorithm is required to eliminate congestion in a "natural" way by being uniform. We also prove that the tradeoffs are asymptotically optimal for uniform algorithms. Furthermore, for uniform algorithms, we find that the routing table size of O(log sub 2 n) is a magic threshold point that separates two different "state-efficiency" regions. Our third result is to study the exact (instead of asymptotic) optimal tradeoffs for uniform algorithms. We propose a new routing algorithm that reduces the routing table size and the network diameter of Chord both by 21.4 without introducing any other protocol overhead, based on a novel number-theory technique. Our final result is to present Ulysses, a congestion-free nonuniform algorithm that achieves a better asymptotic "state-efficiency" tradeoff than existing schemes in the probabilistic sense, even under dynamic node joins leaves. Dipsea is a modular architecture for building a Distributed Hash Table (DHT). A DHT is a large hash table that is cooperatively maintained by a large number of machines communicating over the Internet. Decentralization and automatic re-configuration are two key design goals for a DHT. The architecture of Dipsea consists of three layers: ID Management, Overlay Routing and Data Management. The Overlay Routing layer consists of three modules: Emulation Engine, Ring Management and Choice of Long-Distance Links. Efficient algorithms for ID Management are designed—these algorithms require few messages, require few re-assignments of existing IDs and ensure that the hash table is divided among the participating machines as evenly as possible. Ring Management ensures that participating machines establish connections among themselves, as a function of their IDs, to form a fault-tolerant ring. The Emulation Engine is responsible for “emulation” of arbitrary families of routing networks. It handles issues arising out of dynamism (arrival and departure of participating machines), scale (variation in the average number of participating machines) and physical network proximity. Choice of Long-Distance Links allows a DHT to choose any family of routing networks (deterministic or randomized) for emulation. Several deterministic and randomized routing networks are designed and analyzed. Among these are Symphony (one of the first randomized DHT routing networks), Papillon (a deterministic routing network that guarantees asymptotically optimal route lengths with greedy routing for a fixed out-degree of nodes), and Mariposa (a randomized routing network that also guarantees optimal route lengths for a given out-degree of nodes). Large-scale distributed systems are hard to deploy, and distributed hash tables (DHTs) are no exception. To lower the barriers facing DHT-based applications, we have created a public DHT service called OpenDHT. Designing a DHT that can be widely shared, both among mutually untrusting clients and among a variety of applications, poses two distinct challenges. First, there must be adequate control over storage allocation so that greedy or malicious clients do not use more than their fair share. Second, the interface to the DHT should make it easy to write simple clients, yet be sufficiently general to meet a broad spectrum of application requirements. In this paper we describe our solutions to these design challenges. We also report our early deployment experience with OpenDHT and describe the variety of applications already using the system. This paper uses big data and machine learning for the real-time management of Internet scale quality-of-service (QoS) route optimisation with an overlay network. Based on the collection of data sampled every 2 min over a large number of source–destinations pairs, we show that intercontinental Internet protocol (IP) paths are far from optimal with respect to QoS metrics such as end-to-end round-trip delay. We, therefore, develop a machine learning-based scheme that exploits large scale data collected from communicating node pairs in a multihop overlay network that uses IP between the overlay nodes, and selects paths that provide substantially better QoS than IP. Inspired from cognitive packet network protocol, it uses random neural networks with reinforcement learning based on the massive data that is collected, to select intermediate overlay hops. The routing scheme is illustrated on a 20-node intercontinental overlay network that collects some @math measurements per week, and makes scalable distributed routing decisions. Experimental results show that this approach improves QoS significantly and efficiently. Mobile ad-hoc networks (MANETs) and distributed hash-tables (DHTs) share key characteristics in terms of self organization, decentralization, redundancy requirements, and limited infrastructure. However, node mobility and the continually changing physical topology pose a special challenge to scalability and the design of a DHT for mobile ad-hoc network. The mobile hash-table (MHT) [9] addresses this challenge by mapping a data item to a path through the environment. In contrast to existing DHTs, MHT does not to maintain routing tables and thereby can be used in networks with highly dynamic topologies. Thus, in mobile environments it stores data items with low maintenance overhead on the moving nodes and allows the MHT to scale up to several ten thousands of nodes.This paper addresses the problem of churn in mobile hash tables. Similar to Internet based peer-to-peer systems a deployed mobile hash table suffers from suddenly leaving nodes and the need to recover lost data items. We evaluate how redundancy and recovery technique used in the internet domain can be deployed in the mobile hash table. Furthermore, we show that these redundancy techniques can greatly benefit from the local broadcast properties of typical mobile ad-hoc networks. The objective of this paper is to introduce a model to guide the analysis of the impact of churn in P2P networks. Using this model, a variety of node membership scenarios is created. These scenarios are used to capture and analyze the performance trends of chord, a distributed hash table (DHT) based resource lookup protocol for peer-to-peer overlay networks. The performance study focuses both on the performance of routing and content retrieval. This study also identifies the limitations of various churn-alleviating mechanisms, frequently proposed in the literature. The study highlights the importance of the content nature and access pattern on the performance of P2P, DHT-based overlay networks. The results show that the type of content being accessed and the way the content is accessed has a significant impact on the performance of P2P networks Structured peer-to-peer overlay networks such as CAN, Chord, Pastry, and Tapestry can be used to implement Internet-scale application-level multicast. There are two general approaches to accomplishing this: tree building and flooding. This paper evaluates these two approaches using two different types of structured overlay: 1) overlays which use a form of generalized hypercube routing, e.g., Chord, Pastry and Tapestry, and 2) overlays which use a numerical distance metric to route through a Cartesian hyperspace, e.g., CAN. Pastry and CAN are chosen as the representatives of each type of overlay. To the best of our knowledge, this paper reports the first head-to-head comparison of CAN-style versus Pastry-style overlay networks, using multicast communication workloads running on an identical simulation infrastructure. The two approaches to multicast are independent of overlay network choice, and we provide a comparison of flooding versus tree-based multicast on both overlays. Results show that the tree-based approach consistently outperforms the flooding approach. Finally, for tree-based multicast, we show that Pastry provides better performance than CAN. This paper addresses the problem of churn--the continuous process of node arrival and departure--in distributed hash tables (DHTs). We argue that DHTs should perform lookups quickly and consistently under churn rates at least as high as those observed in deployed P2P systems such as Kazaa. We then show through experiments on an emulated network that current DHT implementations cannot handle such churn rates. Next, we identify and explore three factors affecting DHT performance under churn: reactive versus periodic failure recovery, message timeout calculation, and proximity neighbor selection. We work in the context of a mature DHT implementation called Bamboo, using the ModelNet network emulator, which models in-network queuing, cross-traffic, and packet loss. These factors are typically missing in earlier simulation-based DHT studies, and we show that careful attention to them in Bamboo's design allows it to function effectively at churn rates at or higher than that observed in P2P file-sharing applications, while using lower maintenance bandwidth than other DHT implementations. We consider the problem of routing in a delay tolerant network (DTN) in the presence of path failures. Previous work on DTN routing has focused on using precisely known network dynamics, which does not account for message losses due to link failures, buffer overruns, path selection errors, unscheduled delays, or other problems. We show how to split, replicate, and erasure code message fragments over multiple delivery paths to optimize the probability of successful message delivery. We provide a formulation of this problem and solve it for two cases: a 0 1 (Bernoulli) path delivery model where messages are either fully lost or delivered, and a Gaussian path delivery model where only a fraction of a message may be delivered. Ideas from the modern portfolio theory literature are borrowed to solve the underlying optimization problem. Our approach is directly relevant to solving similar problems that arise in replica placement in distributed file systems and virtual node placement in DHTs. In three different simulated DTN scenarios covering a wide range of applications, we show the effectiveness of our approach in handling failures. There are several analytical results on distributed hash tables (DHTs) that can tolerate Byzantine faults. Unfortunately, in such systems, operations such as data retrieval and message sending incur significant communication costs. For example, a simple scheme used in many Byzantine fault-tolerant DHT constructions of @math nodes requires @math messages, this is likely impractical for real-world applications. The previous best known message complexity is @math in expectation , however, the corresponding protocol suffers from prohibitive costs owing to hidden constants in the asymptotic notation and setup costs. In this paper, we focus on reducing the communication costs against a computationally bounded adversary. We employ threshold cryptography and distributed key generation to define two protocols both of which are more efficient than existing solutions. In comparison, our first protocol is deterministic with @math message complexity and our second protocol is randomized with expected @math message complexity. Further, both the hidden constants and setup costs for our protocols are small and no trusted third party is required. Finally, we present results from micro benchmarks conducted over PlanetLab showing that our protocols are practical for deployment under significant levels of churn and adversarial behaviour. The field of structured P2P systems has seen fast growth upon the introduction of Distributed Hash Tables (DHTs) in the early 2000s. The first proposals, including Chord, Pastry, Tapestry, were gradually improved to cope with scalability, locality and security issues. By utilizing the processing and bandwidth resources of end users, the P2P approach enables high performance of data distribution which is hard to achieve with traditional client-server architectures. The P2P computing community is also being actively utilized for software updates to the Internet, P2PSIP VoIP, video-on-demand, and distributed backups. The recent introduction of the identifier-locator split proposal for future Internet architectures poses another important application for DHTs, namely mapping between host permanent identity and changing IP address. The growing complexity and scale of modern P2P systems requires the introduction of hierarchy and intelligence in routing of requests. Structured Peer-to-Peer Systems covers fundamental issues in organization, optimization, and tradeoffs of present large-scale structured P2P systems, as well as, provides principles, analytical models, and simulation methods applicable in designing future systems. Part I presents the state-of-the-art of structured P2P systems, popular DHT topologies and protocols, and the design challenges for efficient P2P network topology organization, routing, scalability, and security. Part II shows that local strategies with limited knowledge per peer provide the highest scalability level subject to reasonable performance and security constraints. Although the strategies are local, their efficiency is due to elements of hierarchical organization, which appear in many DHT designs that traditionally are considered as flat ones. Part III describes methods to gradually enhance the local view limit when a peer is capable to operate with larger knowledge, still partial, about the entire system. These methods were formed in the evolution of hierarchical organization from flat DHT networks to hierarchical DHT architectures, look-ahead routing, and topology-aware ranking. Part IV highlights some known P2P-based experimental systems and commercial applications in the modern Internet. The discussion clarifies the importance of P2P technology for building present and future Internet systems. Several recent research results describe how to design Distributed Hash Tables (DHTs) that are robust to adversarial attack via Byzantine faults. Unfortunately, all of these results require a significant blowup in communication costs over standard DHTs. For example, to perform a lookup operation, all such robust DHTs of which we are aware require sending O(log^3n) messages while standard DHTs require sending only O(logn), where n is the number of nodes in the network. In this paper, we describe protocols to reduce the communication costs of all such robust DHTs. In particular, we give a protocol to reduce the number of messages sent to perform a lookup operation from O(log^3n) to O(log^2n) in expectation. Moreover, we also give a protocol for sending a large (i.e. containing @W(log^4n) bits) message securely through a robust DHT that requires, in expectation, only a constant blowup in the total number of bits sent compared with performing the same operation in a standard DHT. This is an improvement over the O(log^2n) bit blowup that is required to perform such an operation in all current robust DHTs. Both of our protocols are robust against an adaptive adversary. This paper proposes a routing algorithm that enhances throughput and decreases end-to-end delay in industrial cognitive radio sensor networks (ICRSNs) based on ISA100.11a. In ICRSNs, the throughput is downgraded by interference from primary networks. The proposed routing algorithm is targeted at large-scale networks where data are forwarded through different clusters on their way to the sink. By estimating the maximum throughput for each path, the data can be forwarded through the most optimal path. Simulation results show that our scheme can enhance throughput and decrease end-to-end delay. In classical routing strategies for multihop mobile wireless networks packets are routed on a pre-defined route usually obtained by a shortest path routing protocol. In opportunistic routing schemes, for each packet and each hop, the next relay is found by dynamically selecting the node that captures the packet transmission and which is the nearest to the destination. Such a scheme allows each packet to take advantage of the local pattern of transmissions and fadings at any slot and at any hop. The aim of this paper is to quantify and optimize the potential performance gains of such opportunistic routing strategies compared with classical routing schemes. The analysis is conducted under the following lower layer assumptions: the Medium Access (MAC) layer is a spatial version of Aloha which has been shown to scale well for large multihop networks; the capture of a packet by some receiver is determined by the Signal over Interference and Noise Ratio (SINR) experienced by the receiver. The paper contains a detailed simulation study which shows that such time-space opportunistic schemes very significantly outperform classical routing schemes. It also contains a mathematical study where we show how to optimally tune the MAC parameters so as to minimize the average number of time slots required to carry a typical packet from origin to destination on long paths. We show that this optimization is independent of network density. The throughput of wireless networks can be significantly improved by multi-channel communications compared with single-channel communications since the use of multiple channels can reduce interference influence. In this paper, we study interference-aware topology control and QoS routing in IEEE 802.11-based multi-channel wireless mesh networks with dynamic traffic. Channel assignment and routing are two basic issues in such networks. Different channel assignments can lead to different network topologies. We present a novel definition of co-channel interference. Based on this concept, we formally define and present an effective heuristic for the minimum INterference Survivable Topology Control (INSTC) problem which seeks a channel assignment for the given network such that the induced network topology is interference-minimum among all K-connected topologies. We then formulate the Bandwidth-Aware Routing (BAR) problem for a given network topology, which seeks routes for QoS connection requests with bandwidth requirements. We present a polynomial time optimal algorithm to solve the BAR problem under the assumption that traffic demands are splittable. For the non-splittable case, we present a maximum bottleneck capacity path routing heuristic. Simulation results show that compared with the simple common channel assignment and shortest path routing approach, our scheme improves the system performance by 57 on average in terms of connection blocking ratio.