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Abstract-In contrast to unicast routing, high-throughput reliable multicast routing in wireless mesh networks (WMNs) has received little attention. There are two primary challenges to supporting high-throughput, reliable multicast in WMNs. The first is no different from unicast: wireless links are inherently lossy due to varying channel conditions and interference. The second, known as the "crying baby" problem, is unique to multicast: the multicast source may have varying throughput to different multicast receivers, and hence trying to satisfy the reliability requirement for poorly connected receivers can potentially result in performance degradation for the rest of the receivers.In this paper, we propose Pacifier, a new high-throughput reliable multicast protocol for WMNs. Pacifier seamlessly integrates four building blocks, namely, tree-based opportunistic routing, intra-flow network coding, source rate limiting, and roundrobin batching, to support high-throughput, reliable multicast routing in WMNs, while at the same time effectively addresses the "crying baby" problem. Our evaluations show that Pacifier increases the average throughput over a practical, state-of-the-art reliable network coding-based protocol MORE by 171%, while improving the throughput of well-connected receivers by up to a factor of 20.

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In this paper, we develop a fast resource allocation algorithm that takes advantage of intra-session network coding. The algorithm maximizes the total utility of multiple unicast (or multicast) sessions subject to capacity constraints, where packets are coded within each session. Our solution is a primal solution that does not use duality or congestion prices. Thus, it does not require building up queues to achieve the optimal resource allocation. Hence, the queueing delay of the packets can be tightly controlled. The existing primal solution in the literature requires a separate graph-theoretic algorithm to find the min-cut of each session, whose complexity grows quadratically with the total number of nodes. In contrast, we provide a new coded-feedback approach whose complexity grows only linearly with the total number of nodes. More explicitly, by letting the ACK/feedback packets on the return paths also carry coding coefficients as does the forward coded traffic, key network information can be obtained more efficiently, which leads to a fast resource allocation scheme fully integrated with the network coding operation.

In the face of an explosive increase in the number of IoT devices, the IoT model using blockchain technology, like the traditional IoT system, has a common problem, that is, the communication quality is seriously affected by various interferences, which directly limits the improvement of the service quality of the blockchain-enabled IoT system. Therefore, it is of great practical significance to study the interference problem in the existing Internet of Things system using blockchain technology and propose methods to reduce interference. This paper compares and analyzes the performance of two-slot and three-slot network coding enhanced systems, and designs a new MAC layer protocol for blockchain-enabled IoT systems based on network coding technology. On this basis, through enhanced information transmission at the MAC layer and network coding at the physical layer, the multi-layer collaborative communication method is used to reduce the interference between the IoT system devices enabled by the blockchain. The simulation results show that the use of network coding technology can effectively reduce the mutual interference between data sending nodes in the blockchain-enabled IoT system.

Heuristic search is the process of searching a state space under the guidance of an evaluation function. Most research to date on parallelizing heuristic search algorithms has emphasized system problems such as load balancing and reduction in memory use. In this paper, a theoretical analysis of a new autonomous parallel heuristic search algorithm is introduced. Rather than simply dividing the search space among the processors, the processors share information that monitors the progress of the search and use consensus to limit the amount of time spent in expanding nodes that are not on the optimal path. Each processor uses a different admissible heuristic function, and it is shown that the expected number of nodes generated by each processor in the course of the search is reduced by a factor that reflects the consensus among the processors. The asynchronous behavior of the algorithm eliminates synchronization delays.

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