A Framework for Integrating the Distributed Hash Table (DHT) with an Enhanced Bloom’s Filter in Manet

The Bloom filter is a data structure which the characteristics of contents is expressed by a bit pattern. The Bloom filter has become attractive as one of the methods of looking up data in the distributed system. Since two or more keywords can be used in the method based on the Bloom filter, it is more flexible than the distributed hash table (DHT). Especially, the key aspect of the structured Bloom filter is that the number of query forwarding is fixed. In the previous research, the ring of the Bloom filter, which is like Chord ring, was proposed. However, the node in the ring must maintain many filters corresponding to the number of nodes. In this paper, we propose the tree structured Bloom filter and evaluated the performance of the query forwarding. We also propose similarity-based tree management method which is effective to reduce the cost of reconstruction of the tree. To evaluate our method, the size of filter information and the number of average hops of query forwarding in this research are compared to the existing research. The tree reconstruction cost is also evaluated by simulation.

The Bloom filter has become attractive as one of the methods of looking up data in the distributed system. Since two or more keywords can be used in the method based on the Bloom filter, it is more flexible than the distributed hash table (DHT). Especially, the key aspect of the structured Bloom filter is that the number of query forwarding is fixed. In the research of the past, the ring of the Bloom filter which is like the Chord structure is proposed. However, the node in the ring must maintain many filters corresponding to the number of nodes. In this research, the Bloom filter based on the tree structure is proposed. The filter information managed in the node is reduced, and the size of information in this research is compared to the existing research.

Distributed Hash Tables (DHTs) prove valuable for distributed architectures by providing distributed information lookup, routing, and data storage while promising good scalability and robustness at the same time. From this point of view, a DHT could be seen as a basic service that can be used to build distributed applications. Whereas today no widely deployed and publicly accessible basic DHT service exists and thus DHT- based applications have to deploy their very own DHT networks, DHTs consisting of millions of peers are formed by file sharing clients. Although the interfaces of typical DHTs used for file sharing are too narrow, a basic DHT service could probably be created by bundling a suitable client implementation with file sharing software. In this paper, we evaluate whether a basic DHT service could suit the needs of DHT- based applications in terms of stability, number of participating peers, the peers'' session lengths, geographical distribution and peer connectivity when deployed similar to DHTs driven by file sharing. As these metrics mostly depend on end user behavior rather than on the DHT protocol, we report on measurement results gathered from monitoring of the BitTorrent Mainline client''s DHT over six months. We analyze which metrics would fit a basic DHT service and which could prove problematic. Furthermore, we discuss resulting technical requirements for an appropriate DHT protocol.

Distributed hash tables (DHTs) have proven to be a novel and efficient platform for building a variety of scalable and robust distributed applications like content sharing and location in the Internet. Similar to those in the Internet, distributed applications and network services in mobile ad hoc networks (MANETs) can potentially benefit from the deployment of a DHT. However, bandwidth limitations, node mobility, and multi access interference pose unique challenges to deploying such DHTs in MANETs. In this paper, we first study how to efficiently implement DHTs in MANETs. We explore two disparate design options: the simple approach of directly overlaying a DHT on top of a MANET multi-hop routing protocol, and Ekta which integrates a DHT with a multi-hop routing protocol at the network layer. Second, we examine the efficiency of DHT substrates in supporting applications in MANETs by examining the performance of a resource discovery application built on top of Ekta with one that directly uses physical layer broadcast. Such a study answers the fundamental question of whether a DHT substrate can be more efficient in supporting applications than a physical layer broadcast-based protocol, since in MANETs, DHT protocols effectively rely on physical layer broadcast to discover and maintain routes.

The maintaining overheads of Distributed Hash Table (DHT) topology have recently received considerable attention. This paper presents a novel SHT (Session Heterogeneity Topology) model, in which DHT is reconstructed with session heterogeneity. SHT clusters nodes by means of session heterogeneity among nodes and selects the stable nodes as the participants of DHT. With an evolving process, this model gradually makes DHT stable and reliable. Therefore the high maintaining overheads for DHT are effectively controlled. Simulation with real traces of session distribution showed that the maintaining overheads are reduced dramatically and that the data availability is greatly improved.

Recent research has shown that one can use Distributed Hash Tables (DHTs) to build scalable, robust and efficient applications. One question that is often left unanswered is that of simplicity of implementation and deployment. In this paper, we explore a case study of building an application for which ease of deployment dominated the need for high performance. The application we focus on is Place Lab, an end-user positioning system. We evaluate whether it is feasible to use DHTs as an application-independent building block to implement a key component of Place Lab: its "mapping infrastructure." We present Prefix Hash Trees, a data structure used by Place Lab for geographic range queries that is built entire on top of a standard DHT. By strictly layering Place Lab's data structures on top of a generic DHT service, we were able to decouple the deployment and management of Place Lab from that of the underlying DHT. We identify the characteristics of Place Lab that made it amenable for deploying in this layered manner, and comment on its effect on performance.

P2P systems can be used to provide a wide spectrum of traditional and novel applications. These systems are built around distributed hash tables (DHTs) that allow them to achieve efficient storage and retrieval of resources. A DHT is a data structure whose storage is distributed among network peers. Chord and Kademlia are two relevant examples of such DHTs. A limiting factor for the proper operation of P2P networks is the aggregate effect of peer arrivals and departures. This phenomenon is called churn and it negatively affects the quality of the services provided by DHTs. The lookup service, for instance, is a function that receives a resource ID as the input and determines the pointer to the holder of such resource. This service may fail if the nodes that store parts of a DHT leave the network. In this work we study the performance of the lookup service of Chord and Kademlia in simulation scenarios with different peer online times. We found that, by making use of long-lived peers in the network structure, Kademlia achieves better performance than Chord. Our results suggest that this benefit is obtained even with a low fraction of long-lived peers.

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.

Nowadays, researchers try to verify their ideas through the real world wide Internet instead of simulate those in their own computer or labs. Recent research has shown that researcher can use overlay Distributed Hash Tables (DHTs) to run their applications, such as scalable, robust and efficient. Unfortunately, a would-be developer cannot easily deploy a DHT though many research prototype DHT implementations are available. Some worldwide platforms provide publicly accessible DHT service. Those kinds of platforms can issue at least put and get operations to any DHT node, which processes the operations on their behalf in contrast to the usual DHT model. Since just a few experts are up on those services, there are lots of problems puzzled new researchers. This paper introduces overlay DHT test-platform, points out the problems researchers would meet and figures out the solutions.

Hierarchical packet classification using a Bloom filter and rule-priority tries

In large-scale wireless networks, efficient file searching mechanisms are essential for users. Many studies have been done on a distributed hash tables (DHTs) which are one kind of peer-to-peer system. I n DHT networks, we can certainly and effectively get the desired files i f they exist. However, much communication traffic comes from multi-word searches. If we increase the storage redundancy, we can reduce the traffic. However, storage constrains of mobile devices make doing so impossible. I n our previous work, we proposed a divided bloom filter to reduce the traffic in DHTs. However, the effect of divided bloom filters depends strongly on their parameters, and optimizing them is difficult. Hence, we have developed and tested the method to determine optimum parameters of divided bloom filters.

To realize huge-scale information services, many Distributed Hash Table (DHT) based systems have been proposed. For example, there are some proposals to manage item-level product traceability information with DHTs. In such an application, each entry of a huge number of item-level IDs need to be available on a DHT. To ensure data availability, the soft-state approach has been employed in previous works. However, this does not scale well against the number of entries on a DHT. As we expect 1010 products in the traceability case, the soft-state approach is unacceptable. In this paper, we propose Distributed-to-Distributed Data Copy (D3C). With D3C, users can reconstruct the data as they detect data loss, or even migrate to another DHT system. We show why it scales well against the number of entries on a DHT. We have confirmed our approach with a prototype. Evaluation shows our approach fits well on a DHT with a low rate of failure and a huge number of data entries.

Degree, diameter and congestion are important measures of distributed hash table (DHT) schemes for peer-to-peer networks. Many proposed DHT schemes are based on some traditional interconnection topologies and the Kautz graph is a topology with good properties such as optimal network diameter. In this paper, FissionE, a novel DHT scheme based on the Kautz graph, is proposed. FissionE is the first constant degree and O (log N ) diameter DHT scheme with (1+ o (1))-congestion. FissionE shows that the DHT scheme with constant degree and constant congestion can achieve O (log N ) diameter, which is better than the lower bound Ω ( N 1/d ) conjectured before. The average degree of FissionE is 4 and the diameter is 2*log 2 N , and the average routing path length is about log 2 N , . The average path length of FissionE is shorter than CAN or Koorde with the same degree when the P2P network is large scale.

With the growing adoption of cloud services, organizations are increasingly outsourcing their system log management to cloud service providers (CSPs). While this approach offers cost efficiency and scalability, it introduces critical challenges related to the confidentiality, searchability, and integrity of sensitive log data. Specifically, existing solutions fall short in supporting fine-grained Boolean keyword search, dynamic access control, and verifiable result integrity over encrypted log records. To address these challenges, we propose EVSEB—an efficient and verifiable searchable encryption framework for encrypted cloud-hosted logs. EVSEB supports fine-grained multi-keyword Boolean search, privacy-preserving access control, and per-file integrity verification with minimal overhead. At its core, EVSEB introduces a hybrid indexing model that integrates a hierarchical log-type classification tree, Bloom filters, and inverted indexes to reduce search space and accelerate query execution. Access control is enforced through blockchain-based smart contracts that securely validate encrypted user tokens. For integrity assurance, EVSEB combines an off-chain distributed hash table (DHT) and an on-chain Merkle root to detect tampering at the level of individual log files. Experimental evaluion demonstrates that our proposed EVSEB outperforms existing solutions in terms of search under increasing keyword and file load, and integrity verification. This substantiates the practicality of our proposed scheme in implementing a searchable encryption and access solution for large-scale encrypted log management in cloud environments.

Distributed hash table (DHT) P2P systems provide flexible management of large scale distributed systems. They also provide efficient object localization given its key. However, they don't provide high level query languages to formulate such location queries. Recent efforts have been made to improve such querying capabilities. Nevertheless, most of the proposed solutions are based on special hashing functions or on an additional level of peers. This work presents PinS, a P2P interrogation and indexation middleware for DHT based P2P systems. It improves data sharing in such systems by supporting declarative queries and some facilities on data management without using particular hash functions or other requirements. Location queries may be conjunctions or disjunctions of conditions including comparison terms, and users may specify some evaluation constraints. Comprehensive or partial answers are provided. PinS supports pre-defined and customized attributes to describe objects and allows sharing objects with restricted access. Additionally, PinS enables several query execution strategies and proposes the use of indexes to improve comparison queries support. Our performance analysis shows the scalability of the system. In particular, the complexity of the evaluation of conjunctive queries is independent of the number of objects registered in the system.