A Novel Symmetric Algorithm for Process Synchronization in Distributed Systems

A scheduler for SCADA-based multi-source fusion systems

“…The proposals that focus on resource that are connected through a communications network [11,23,36,38,46,47,50] do not seem easy to adapt because they depend on a variety of parameters that are highly dependent on the network and difficult to extrapolate to other contexts, e.g., signal strength or waveform. The proposals that focus on general resources [3,5,35,49,56,57,60] might be applicable by mapping each rendez-vous onto a shared resource for which the agents have to compete; the problem is that they were not designed to deal with resources that must be shared by two or more agents. The proposals that focus on agents [12,14,22,24,31,41,43,55,58,59] are not applicable because their goal is to guarantee that agents can progress by allocating them to the computing devices that have more computing power available, independently from whether they co-ordinate or not with others; in these proposals, an agent that is readying a rendez-vous is considered to be waiting for input/output, which excludes it from the collection of agents whose progress must be guaranteed.…”

“…The idea to enforce fairness using a scheduler was soon adopted in the context of distributed systems [48] , where fairness is used to ensure that no resource remains idle forever or that no agent can starve forever. In the context of information fusion, there are some proposals that focus on resources that can be accessed by means of specificpurpose IoT networks [38,47] or general-purpose communication networks [11,23,36,46,50] ; there are also some proposals that deal with arbitrary resources [3,5,35,49,56,57,60] . Regarding agents, there are several proposals that focus on allocating them to the data centres [12] , the machines [22,31,41,55,58,59] , or the cores [14,24,43] that have more computing power available, since this helps prevent starvation.…”

“…The previous problem is related to a liveness property called fairness [16,25,34,53]. In the literature, there are many proposals to enforce fairness, but most of them cannot be adapted to our context: some proposals were designed to deal with two-way rendez-vouses only [3,5,35,49,56,57,60], but typical rendez-vouses in our context coordinate many more agents; others require to instrument the agents to build a scheduler into them [1,4,7,10,26], which can only be simulated by means of wrappers that are not generally possible to implement in low-end computing boards; some of them [4,7] cannot deal with rendezvouses that get intermittently enabled or disabled along an execution, which hinders applying them to our context; and some of them require to use shared memory [42], which is an advanced hardware feature that is not available in low-end computing boards. There are two proposals that could be adapted [30,45], but our experimental analysis confirms that they are not efficient enough in our context because they drove our experimental system into as many as 1 102.77 and 1 458.65 criticalfailure states per hour, respectively.…”