Laurent George

Wireless connectivity standards have been developed by standardizing bodies to meet the requirements of various applications. A wireless transceiver should be equipped with a Radio Frequency (RF) transceiver to support a wireless standard. Traditional RF transceivers are designed and implemented on a radio chip or an embedded module in a System-on-a-Chip (SoC), ensuring small size, high performance, low power consumption, and cost. However, this traditional implementation design limits directly or indirectly the programmability and flexibility of the RF transceivers. An alternative solution to implement RF transceivers is using Software Defined Radio (SDR) platforms. In the market, SDR platform hardware exists with different configurations, performance, cost, size, etc., making it hard to select the minimum SDR platform necessary to satisfy the wireless standard requirements. This paper aims to provide a list of well-known General Purpose Processor (GPP) based SDR platforms that meet the minimum specifications of selected wireless standards. To this end, we first review the characteristics of selected wireless technologies. Then, we investigate existing SDR platform architecture and their maximal performance in terms of the frequency range, bandwidth, symbol rate, bitrate, and latency support. Finally, we intersect the wireless standard requirements with the corresponding SDR platform parameters and provide a list of GPP-based SDR platforms for some existing wireless technology implementations. All investigations related to the frequency, bandwidth, symbol rate, and bitrate parameters are supported by theoretical results, whereas latency results are obtained from experiments by benchmarking existing implementations.

Consider uniprocessor platforms, the scheduling of synchronous implicit deadline periodic task sets and the dual priority scheme where each task is assigned two fixed priorities. That is, at run time each task starts executing using its primary priority and is promoted if not completed at an intermediate deadline. We present counter-intuitive examples illustrating how difficult this scheduling problem is. We propose a preprocessing approach to remove from the scheduling problem lowest priority viable tasks as defined by Audsley's procedure. We revisit one solution called RM + RM conjectured optimal. We propose a procedure to compute promotion deadlines based on multiple simulations over an hyperperiod called FDMS. That solution has an exponential time complexity but an experimental success ratio of 100%. Then we propose a new sub-optimal solution to assign priorities called 1 /RM + RM along with a very simple promotion deadline assignment scheme called RML for which no simulation are required, the procedure is simple and the success ratio is close to 99.99%. We show that the method is fast and scalable to very large task sets which makes it ideal for practical applications.

Energy efficiency in factories is a new paradigm arising with automatic Demand Response (DR) protocols like OpenADR that enables energy providers to ask their clients to reduce their power consumption for a given time. DR is used to smooth peaks of energy demand at country level by energy providers and the clients get paid for not consuming. Upon reception of a DR, a client should decide in a bounded time if he agrees on DR and for how long. In this paper, we characterize a DR scheduling problem for a production line with available power constraint. Our objective is to respect the DR constraint in a way that its impact on production rate (number of finished items per time unit) is limited as much as possible. To do so, we first propose a scheduling algorithm based on an exhaustive search approach to find an optimal schedule. As complexity of this approach is high, we then develop a heuristic approach based on Integer Linear Programming (ILP) model to find sub-optimal solutions. We conduct simulations to compare performances of the two approaches in terms of production rate, run time and monetary gain.