#Mac not waking for network access mac#

This probability is selected in order to maximize the LSN throughput. To cope with these conditions, SA-MAC introduces the following two rules: (i) During a transmission slot, nodes that are candidates to contend for the channel awake with probability, where is the nodesвЂ™ grade.

#Mac not waking for network access mac#

Unlike previous works, the proposed Selective-Awakening MAC (SA-MAC) protocol is specifically designed for IoT scenarios, where node density and traffic load can be high. In this paper, we present a synchronized duty-cycled protocol with pipelined scheduling where nodes selectively awake depending on node density and traffic load conditions. This way, a packet can traverse a source-to-sink path in a single cycle if there are no other packets at the queues of the nodes along its path, which is the main advantage of this strategy over other proposals. Grade schedules are arranged in such a way that packets can be forwarded from one grade to another in a pipelined fashion. In pipelined scheduling, nodes are classified according to their grade (distance in hops to the sink node) and nodes with the same grade share the same schedule namely, they synchronously enter the different modes in the following sequence: one reception slot, one transmission slot, and sleeping slots. introduced the PRI-MAC protocol which implements a pipelined scheduling as a complement for a duty-cycled protocol that is based on S-MAC. Building on the success of duty-cycling, complementary techniques have been proposed to further improve the performance of LSN for instance, Tong et al. As in any WSN, one of the main goals when designing an LSN is to provide high throughput in an energy-efficient way, which could be achieved by defining appropriate Medium Access Control (MAC) protocols.ДЄmong the large body of work devoted to designing efficient MAC protocols that improve energy consumption, synchronized duty-cycling protocols have been shown to be particularly effective in the context of MANETs, WSNs, and LSNs.

In particular, when the node density is high, as it is commonly the case when a wide variety of variables are being sensed, the LSN is named a thick LSN. The objective is to extend the lifetime of the road infrastructure, improve safety, decrease commutersвЂ™ travel time, and diminish air pollution in densely populated cities.ДЄs in the previous examples, when the sensing devices are deployed along linear structures, the resulting wireless sensor network (WSN) is usually denoted as a Linear Sensor Network (LSN). In these scenarios, a set of sensors are located along the road infrastructure in order to coordinate urban transport, monitor events that affect mobility, or manage transit through dynamic coordination of traffic lights. IoT applications have also been identified as a mean for fostering smart mobility. With this technology, it is possible to identify leaks along lines or pipelines and optimize the operation of these distribution networks. IoT has been proposed as a core technology for establishing what it is known as Advanced Measurement Infrastructures (AMI) which are responsible for monitoring public distribution networks of water, electricity, or gas. Internet of Things (IoT) is a network paradigm that is playing a key role in the development of smart environments where everyday objects are augmented with computational capabilities and Internet connectivity, so that they can interact with each other in order to share information about the environment, coordinate actions autonomously, and fulfill other specific purposes such as target tracking, medical supervision of patients, and animal monitoring. Such results can be used as a design guideline for future LSN implementations. We also present an analysis by grade (i.e., the number of hops to the sink, which is located at one end of the LSN) that reveals that LSNs exhibit heterogeneous performance depending on the nodesвЂ™ grade. This is particularly true under high node density and high traffic load conditions, which are expected to be common scenarios in the context of IoT applications.

Our results show that SA-MAC significantly outperforms previous proposals in terms of energy consumption, throughput, and packet loss probability. In order to characterize the performance of the proposed protocol, we present a Discrete-Time Markov Chain-based analysis that is validated through extensive discrete-event simulations.

In the proposed protocol, nodes selectively awake depending on node density and traffic load conditions and on the state of the buffers of the receiving nodes. We introduce the Selective-Awakening MAC (SA-MAC) protocol which is a synchronized duty-cycled protocol with pipelined scheduling for Linear Sensor Networks (LSNs).