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Item type:Publication, Access status: without files , TimeCast: real-time many-to-many ata-sharing in low-power wireless distributed systems(2023-07-17); ; ; ; Many-to-many/all-to-all sharing of data is one of the common requirements in any distributed/decentralized system. In low-power wireless distributed systems composed of highly resource-constrained devices, a many-to-many data-sharing strategy needs to be not only efficient but also sufficiently simple in nature. Advancements in the field of synchronous transmission (ST) have proliferated a number of efficient data-sharing strategies for low-power systems. In this work, we first identify the fundamental and simple possible approaches to accomplish the goal. Through extensive simulation-based comparison among them, we demonstrate the superiority of the approach adopted by a strategy called MiniCast where the desired task is achieved through pipelined execution of the one-to-many floods from the designated source nodes. However, through further in-depth study, we identify certain crucial flaws in MiniCast, which are mostly caused by its substandard realization through radio-event-triggered architecture. To circumvent the problems, we propose a new strategy TimeCast where the radio-event-triggered architecture of MiniCast is replaced by a time-triggered architecture. Through rigorous experimental studies in IoT-testbeds, we demonstrate that TimeCast substantially improves the robustness, and thus, due to lesser failures, it achieves all-to-all data-sharing up to 57.1% faster while consuming up to 63.6% lesser radio-on time compared to MiniCast.Publicationtype: Journal Article37 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Start of frame delimiters (SFDs) for simultaneous intra-group one-to-all disseminationIntra-group spreading is one of the common and frequent needs in many decentralized communication protocols. Such spreading is useful for quick and local dissemination of information among different clusters in large-scale decentralized systems like the Internet-of-Things (IoT). Complex decentralized protocols can carefully exploit such localized dissemination as a base unit for their efficient implementation. However, due to the inherent broadcast nature of wireless communication, efficient and simultaneous execution of multiple intra-group disseminations is difficult. In this work, we propose a novel and simple way to completely hide a wireless transmission without changing any channel or frequency. Next, we use this for supporting simultaneous intra-group disseminations. Rigorous evaluation of the proposed strategy over testbeds show significant improvement of upto 60% in reliability with similar average latency and radio-on time in comparison to the baseline where no additional mechanism is adopted for separation of intra-group communications.Publicationtype: Conference Paper13 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Efficient many-to-many data sharing using synchronous transmission and TDMAAchieving fast and efficient many-to-many communication is one of the most complex communication problems, especially in wireless systems. A compact form of many-to-many communication in a distributed system has the potential to bring huge benefit to many distributed algorithms and protocols. Many-to-many communication can be implemented as a sequential instantiations of a network wide one-to-many communication. One limitation of such an approach is that each individual instance of a one-to-many communication has to be given enough time to propagate through the whole network before the next instance. In addition, there is large overhead in generating the schedule for the sequence of individual one-to-many communications. In this work, we show that many-to-many communication can be more efficiently implemented as many parallel many-to-one communications. In this direction, we first develop an efficient TDMA based many-to-one communication module, and then use it in many-to-many setting. Our approach achieves a minimum about 20% to 50% improvements on latency (radio-on time) over the state-of-the-art solutions in a 90-node wireless sensor network testbed.Publicationtype: Conference Paper13