The rising number of IoT devices is accelerating the research on new solutions that will be able to efficiently deal with unreliable connectivity in highly dynamic computing applications. To improve the overall performance in IoT applications, there are multiple communication solutions available, either proprietary or open source, all of which satisfy different communication requirements. Most commonly, for this kind of communication, developers choose REST HTTP protocol as a result of its ease of use and compatibility with the existing computing infrastructure. In applications where mobility and unreliable connectivity play a significant role, ensuring a reliable exchange of data with the stateless REST HTTP protocol completely depends on the developer itself. This often means resending multiple request messages when the connection fails, constantly trying to access the service until the connection reestablishes. In order to alleviate this problem, in this paper, we combine REST HTTP with random linear network coding (RLNC) to reduce the number of additional retransmissions. We show how using RLNC with REST HTTP requests can decrease the reconnection time by reducing the additional packet retransmissions in unreliable highly dynamic scenarios.
Network coding (NC) can be dated in 2000 @cite_11 , a technique which allows network systems to combine several native messages into one coded message in order to expand the maximum bandwidth utilization. In @cite_10 authors use a network coded protocol operating between the network and transport layers in a wireless network. The results have shown that by using RLNC, this protocol was able to recover from packet losses. In order to improve performances of dynamic IoT scenarios the interesting path is the combination of network coding and fog based computing. Possible applications of NC in IoT and fog based systems have been described in @cite_0 with promosing results reported in @cite_9 , where authors have used NC to improve efficiency of data communication protocols in fog computing wireless sensor environment. In this paper we will explore combination of NC and REST HTTP protocol in IoT to fog communication scenario, as it is still application layer protocol of choice for developers according to multiple research efforts as the one reported in @cite_6 .
@cite_9 @cite_6 @cite_0 @cite_10 @cite_11
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In this paper, we propose an energy-efficient solution for implementing Network Coding (NC) in wireless networks based on the IEEE 802.11 Standard. The proposed mechanism, called GreenCode, allows nodes to duty cycle by switching to a low-power (sleep) state when they overhear coded packet transmissions that will not provide any new information for them. To facilitate the sleep operation, bidirectional transmissions involving both coded and non-coded packets between pairs of sender-receiver nodes are integrated into the operation of GreenCode. Both analytical and simulation results presented in this paper show the high energy efficiency of GreenCode with gains of up to 360 when compared to the existing mechanisms based on the IEEE 802.11 Standard. A communication protocol for fog computing should be efficient, lightweight and customizable. In this work we focus in a communication protocol for fog nodes composed of wireless sensors, which are spatially distributed autonomous sensors monitoring physical or environmental conditions. Problems with data congestion and limited physical resources are common in these networks. For the optimization of data flow, it is important to apply techniques that reduce the transmitted data. We use the network coding technique to demonstrate through experiments the degree of efficiency of data transmission optimization protocols. The experiments were performed through a wireless sensors programming framework composed of TinyOS operating system, NesC programming language and TOSSIM simulator. In addition, we use the Python programming language to simulate the wireless sensor network topology. The results obtained demonstrate a better performance (50 up to 60 ) when the network coding technique is applied to the data communication protocol. The rising number of IoT devices is accelerating the research on new solutions that will be able to efficiently deal with unreliable connectivity in highly dynamic computing applications. To improve the overall performance in IoT applications, there are multiple communication solutions available, either proprietary or open source, all of which satisfy different communication requirements. Most commonly, for this kind of communication, developers choose REST HTTP protocol as a result of its ease of use and compatibility with the existing computing infrastructure. In applications where mobility and unreliable connectivity play a significant role, ensuring a reliable exchange of data with the stateless REST HTTP protocol completely depends on the developer itself. This often means resending multiple request messages when the connection fails, constantly trying to access the service until the connection reestablishes. In order to alleviate this problem, in this paper, we combine REST HTTP with random linear network coding (RLNC) to reduce the number of additional retransmissions. We show how using RLNC with REST HTTP requests can decrease the reconnection time by reducing the additional packet retransmissions in unreliable highly dynamic scenarios. We investigate the performance of delay constrained data transmission over wireless networks without end-to-end feedback. Forward error-correction coding (FEC) is performed at the bit level to combat channel distortions and random linear network coding (RLNC) is performed at the packet level to recover from packet erasures. We focus on the scenario where RLNC re-encoding is performed at intermediate nodes and we assume that any packet that contains bit errors after FEC decoding can be detected and erased. To facilitate explicit characterization of data transmission over network-coded wireless systems, we propose a generic two-layer abstraction of a network that models both bit symbol-level operations at the lower layer (termed PHY-layer) over several heterogeneous links and packet-level operations at the upper layer (termed NET-layer). Based on this model, we propose a network reduction method to characterize the throughput-reliability function of the end-to-end transmission. Our approach not only reveals an explicit tradeoff between data delivery rate and reliability, but also provides an intuitive visualization of the bottlenecks within the underlying network. We illustrate our approach via a point-to-point link and a relay network and highlight the advantages of this method over capacity-based approaches.