The Trinity (, 2007) spam classification system is based on a distributed hash table that is implemented using a structured peer-to-peer overlay. Such an overlay must be capable of processing hundreds of messages per second, and must be able to route messages to their destination even in the presence of failures and malicious peers that misroute packets or inject fraudulent routing information into the system. Typically there is tension between the requirements to route messages securely and efficiently in the overlay. We describe a secure and efficient routing extension that we developed within the I3 ( 2004) implementation of the Chord ( 2001) overlay. Secure routing is accomplished through several complementary approaches: First, peers in close proximity form overlapping groups that police themselves to identify and mitigate fraudulent routing information. Second, a form of random routing solves the problem of entire packet flows passing through a malicious peer. Third, a message authentication mechanism links each message to it sender, preventing spoofing. Fourth, each peer's identifier links the peer to its network address, and at the same time uniformly distributes the peers in the key-space. Lastly, we present our initial evaluation of the system, comprising a 255 peer overlay running on a local cluster. We describe our methodology and show that the overhead of our secure implementation is quite reasonable.
@cite_7 also proposed a routing failure test that tries to determine what nodes are malicious. Their approach also sends multiple copies of the message through diverse routes to ensure message delivery. Our approach is similar but less resource intensive. Our system uses the peer groups to detect faulty routing information, and to ensure that no peer is a choke-point between two other peers. Our system does not attempt to ensure the delivery of all messages, but instead attempts to ensure that some messages will be delivered.
@cite_7
1992467531 2135805607 2115930054 2082674813
We consider the problem of designing an overlay network and routing mechanism that permits finding resources efficiently in a peer-to-peer system. We argue that many existing approaches to this problem can be modeled as the construction of a random graph embedded in a metric space whose points represent resource identifiers, where the probability of a connection between two nodes depends only on the distance between them in the metric space. We study the performance of a peer-to-peer system where nodes are embedded at grid points in a simple metric space: a one-dimensional real line. We prove upper and lower bounds on the message complexity of locating particular resources in such a system, under a variety of assumptions about failures of either nodes or the connections between them. Our lower bounds in particular show that the use of inverse power-law distributions in routing, as suggested by Kleinberg [5], is close to optimal. We also give heuristics to efficiently maintain a network supporting efficient routing as nodes enter and leave the system. Finally, we give some experimental results that suggest promising directions for future work. Finding information in a peer-to-peer system currently requires either a costly and vulnerable central index, or flooding the network with queries. We introduce the concept of routing indices (RIs), which allow nodes to forward queries to neighbors that are more likely to have answers. If a node cannot answer a query, it forwards the query to a subset of its neighbors, based on its local RI, rather than by selecting neighbors at random or by flooding the network by forwarding the query to all neighbors. We present three RI schemes: the compound, the hop-count, and the exponential routing indices. We evaluate their performance via simulations, and find that RIs can improve performance by one or two orders of magnitude vs. a flooding-based system, and by up to 100 vs. a random forwarding system. We also discuss the tradeoffs between the different RI schemes and highlight the effects of key design variables on system performance. We study the problem of data-driven routing and navigation in a distributed sensor network over a continuous scalar field. Specifically, we address the problem of searching for the collection of sensors with readings within a specified range. This is named the iso-contour query problem. We develop a gradient based routing scheme such that from any query node, the query message follows the signal field gradient or derived quantities and successfully discovers all iso-contours of interest. Due to the existence of local maxima and minima, the guaranteed delivery requires preprocessing of the signal field and the construction of a contour tree in a distributed fashion. Our approach has the following properties: (i) the gradient routing uses only local node information and its message complexity is close to optimal, as shown by simulations; (ii) the preprocessing message complexity is linear in the number of nodes and the storage requirement for each node is a small constant. The same preprocessing also facilitates route computation between any pair of nodes where the the route lies within any user supplied range of values. Message delivery in sparse Mobile Ad hoc Networks (MANETs) is difficult due to the fact that the network graph is rarely (if ever) connected. A key challenge is to find a route that can provide good delivery performance and low end-to-end delay in a disconnected network graph where nodes may move freely. This paper presents a multidisciplinary solution based on the consideration of the so-called small world dynamics which have been proposed for economy and social studies and have recently revealed to be a successful approach to be exploited for characterising information propagation in wireless networks. To this purpose, some bridge nodes are identified based on their centrality characteristics, i.e., on their capability to broker information exchange among otherwise disconnected nodes. Due to the complexity of the centrality metrics in populated networks the concept of ego networks is exploited where nodes are not required to exchange information about the entire network topology, but only locally available information is considered. Then SimBet Routing is proposed which exploits the exchange of pre-estimated "betweenness' centrality metrics and locally determined social "similarity' to the destination node. We present simulations using real trace data to demonstrate that SimBet Routing results in delivery performance close to Epidemic Routing but with significantly reduced overhead. Additionally, we show that SimBet Routing outperforms PRoPHET Routing, particularly when the sending and receiving nodes have low connectivity.