Abstract-Named Data Networks provide a clean-slate redesign of the Future Internet for efficient content distribution. Because Internet of Things are expected to compose a significant part of Future Internet, most content will be managed by constrained devices. Such devices are often equipped with limited CPU, memory, bandwidth, and energy supply. However, the current Named Data Networks design neglects the specific requirements of Internet of Things scenarios and many data structures need to be further optimised. The purpose of this research is to provide an efficient strategy to route in Named Data Networks by constructing a Forwarding Information Base using Iterated Bloom Filters defined as I(FIB)F. We propose the use of content names based on iterative hashes. This strategy leads to reduce the overhead of packets. Moreover, the memory and the complexity required in the forwarding strategy are lower than in current solutions. We compare our proposal with solutions based on hierarchical names and Standard Bloom Filters. We show how to further optimise I(FIB)F by exploiting the structure information contained in hierarchical content names. Finally, two strategies may be followed to reduce: (i) the overall memory for routing or (ii) the probability of false positives.
Named Data Networks provide a clean-slate redesign of the Future Internet for efficient content distribution. Because Internet of Things are expected to compose a significant part of Future Internet, most content will be managed by constrained devices. Such devices are often equipped with limited CPU, memory, bandwidth, and energy supply. However, the current Named Data Networks design neglects the specific requirements of Internet of Things scenarios and many data structures need to be further optimised. The purpose of this research is to provide an efficient strategy to route in Named Data Networks by constructing a Forwarding Information Base using Iterated Bloom Filters defined as I(FIB)F. We propose the use of content names based on iterative hashes. This strategy leads to reduce the overhead of packets. Moreover, the memory and the complexity required in the forwarding strategy are lower than in current solutions. We compare our proposal with solutions based on hierarchical names and Standard Bloom Filters. We show how to further optimise I(FIB)F by exploiting the structure information contained in hierarchical content names. Finally, two strategies may be followed to reduce: (i) the overall memory for routing or (ii) the probability of false positives.
Abstract:The main problem studied in this paper is how to design an efficient method for information brokerage in sensor networks that do not use an overlay layer to organize the network and when geo-coordinates are not provided. We present a method for the solution of this problem using Directional Random Walks (DRWs) which main purpose is to construct a straight path of relaying nodes in the network. When two DRWs intersect the information brokerage system is able to proceed with the data exchange. The implementation of DRWs can be done using one or two branches. Our results reflect that the use of the second neighborhood to forward the DRW does not improve its depth. We also prove that the use of two branches for the construction of the DRW improves latency and that higher densities of nodes in the network lead to the construction of shorter paths. We have used permutations on the top of a well-connected network to test the information brokerage system. The results show that our method is good at balancing the load without using a large amount of nodes. Indeed, we show that the behaviour of DRWs is quite similar to Rumor Routing with an infinite memory.
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