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Mobility in ad hoc networks causes frequent link failures, which in turn causes packet losses. TCP attributes these packet losses to congestion. This incorrect inference results in frequent TCP retransmission time-outs and therefore a degradation in TCP performance even at light loads. We propose mechanisms that are based on signal strength measurements to alleviate such packet losses due to mobility. Our key ideas are (a) if the signal strength measurements indicate that a link failure is most likely due to a neighbor moving out of range, in reaction, facilitate the use of temporary higher transmission power to keep the link alive and, (b) if the signal strength measurements indicate that a link is likely to fail, initiate a route re-discovery proactively before the link actually fails. We make changes at the MAC and the routing layers to predict link failures and estimate if a link failure is due to mobility.We also propose a simple mechanism at the MAC layer that can help alleviate false link failures, which occur due to congestion when the IEEE 802.11 MAC protocol is used. We compare the above proactive and reactive schemes and also demonstrate the benefits of using them together and along with our MAC layer extension. We show that, in high mobility, the goodput of a TCP session can be improved by as much as 75% at light loads (when there is only one TCP session in the network) when our methods are incorporated. When the network is heavily loaded (i.e., there are multiple TCP sessions in the network), the proposed schemes can improve the aggregate goodput of the TCP sessions by about 14% -30%, on average.

Peer-to-peer networks have been identified as promising architectural concept for developing search scenarios across digital library collections. Digital libraries typically offer sophisticated search over their local content, however, search methods involving a network of such stand-alone components are currently quite limited. We present an architecture for highly-efficient search over digital library collections based on structured P2P networks. As the standard single-term indexing strategy faces significant scalability limitations in distributed environments, we propose a novel indexing strategy-key-based indexing. The keys are term sets that appear in a restricted number of collection documents. Thus, they are discriminative with respect to the global document collection, and ensure scalable search costs. Moreover, key-based indexing computes posting list joins during indexing time, which significantly improves query performance. As search efficient solutions usually imply costly indexing procedures, we present experimental results that show acceptable indexing costs while the retrieval performance is comparable to the standard centralized solutions with TF-IDF ranking.

There has been an increasing research interest in developing full-text retrieval based on peer-to-peer (P2P) technology. So far, these research efforts have largely concentrated on efficiently distributing an index. However, ranking of the results retrieved from the index is a crucial part in information retrieval. To determine the relevance of a document to a query, ranking algorithms use collection-wide statistics. Term frequency-inverse document frequency (TF-IDF), for example, is based on frequencies of documents containing a given term in the whole collection. Such global frequencies are not readily available in a distributed system. In this paper, we study the feasibility of aggregating global frequencies for a large term vocabulary in a P2P setting. We use a distributed hash table (DHT) for our analysis. Traditional applications of DHTs, such as file sharing, index keys in the order of tens of thousands. Aggregation of a vocabulary consisting of millions of terms poses extreme requirements to a DHT implementation. We study different aggregation strategies and propose optimizations to DHTs to efficiently process large numbers of keys.

There have been many proposals for constructing routing tables for Distributed Hash Tables (DHT).