Airborne Network Data Availability Using Peer to Peer Database Replication on a Distributed Hash Table

The concept of distributing one complex task to several smaller, simpler Unmanned Aerial Vehicles (UAVs) as opposed to one complex UAV is the way of the future for a vast number of surveillance and data collection tasks. One objective for this type of application is to be able to maintain an operational picture of the overall environment. Due to high bandwidth costs, centralizing all data may not be possible, necessitating a distributed storage system such as mobile Distributed Hash Table (DHT). A difficulty with this maintenance is that for an Airborne Network (AN), nodes are vehicles and travel at high rates of speed. Since the nodes travel at high speeds they may be out of contact with other nodes and their data becomes unavailable. To address this the DHT must include a data replication strategy to ensure data availability. This research investigates the percentage of data available throughout the network by balancing data replication and network bandwidth. The DHT used is Pastry with data replication using Beehive, running over an 802.11 wireless environment, simulated in Network Simulator 3. Results show that high levels of replication perform well until nodes are too tightly packed inside a given area which results in too much contention for limited bandwidth

Towards an efficient indexing and searching model for service discovery in a decentralised environment.

Given the growth and outreach of new information, communication, computing and electronic technologies in various dimensions, the amount of data has explosively increased in the recent years. Centralised systems suffer some limitations to dealing with this issue due to all data is stored in central data centres. Thus, decentralised systems are getting more attention and increasing in popularity. Moreover, efficient service discovery mechanisms have naturally become an essential component in both large-scale and small-scale decentralised systems and. This research study is aimed at modelling a novel efficient indexing and searching model for service discovery in decentralised environments comprising numerous repositories with massive stored services. The main contributions of this research study can be summarised in three components: a novel distributed multilevel indexing model, an optimised searching algorithm and a new simulation environment. Indexing model has been widely used for efficient service discovery. For instance; the inverted index is one of the popular indexing models used for service retrieval in consistent repositories. However, redundancies are inevitable in the inverted index which is significantly time-consuming in the service discovery and retrieval process. This theeis proposes a novel distributed multilevel indexing model (DM-index), which offers an efficient solution for service discovery and retrieval in distributed service repositories comprising massive stored services. The architecture of the proposed indexing model encompasses four hierarchical levels to eliminate redundancy information in service repositories, to narrow the searching space and to reduce the number of traversed services whilst discovering services. Distributed Hash Tables have been widely used to provide data lookup services with logarithmic message costs which only require maintenance of limited amounts of routing states. This thesis develops an optimised searching algorithm, named Double-layer No-redundancy Enhanced Bi-direction Chord (DNEB-Chord), to handle retrieval requests in distributed destination repositories efficiently. This DNEB-Chord algorithm achieves faster routing performances with the double-layer routing mechanism and optimal routing index. The efficiency of the developed indexing and searching model is evaluated through theoretical analysis and experimental evaluation in a newly developed simulation environment, named Distributed Multilevel Bi-direction Simulator (DMBSim), which can be used as cost efficient tool for exploring various service configurations, user retrieval requirements and other parameter settings. Both the theoretical validation and experimental evaluations demonstrate that the service discovery efficiency of the DM-index outperforms the sequential index and inverted index configurations. Furthermore, the experimental evaluation results demostrate that the DNEB-Chord algorithm performs better than the Chord in terms of reducing the incurred hop counts. Finally, simulation results demonstrate that the proposed indexing and searching model can achieve better service discovery performances in large-scale decentralised environments comprising numerous repositories with massive stored services.N/