Wireless sensor network, MAC protocol, asynchronous duty cycling, energy efficiency, Markov chain. Receiver-initiated wake-up scheme as well as clear chan.
An asynchronous medium access control (MAC) duty-cycled protocols have higher energy efficiency and lower packet latency than synchronized ones due to reduced idle listening. Moreover, they provide efficient utilization of energy supplied to mobile sensors. They are considered very important in MAC protocols due to the adverse effects of hidden terminals which causes energy consumption in sensor networks. Therefore, in this paper, the impact of hidden terminals on the performance of an asynchronous duty-cycled MAC protocol X-MAC for vehicle-base sensor is investigated via analysis and simulations. We propose a Markov model to analyze the quality-of-service (QoS) parameters in terms of energy consumption, delay, and throughput.
Our analytical model provides QoS parameter values that closely match the simulation results under various network conditions. Our model is more computationally efficient and provides accurate results quickly compared with simulations. More importantly, our model enables the designers to obtain a better understanding of the effects of different numbers of mobile sensor nodes and data arrival rates on the performance of an asynchronous MAC duty-cycled protocol. Vehicular sensor networks (VSNs) allow limited range sensor devices to communicate with each other.
VSNs are promising solutions for specific cases of the Internet of things (IoTs), which allow the integration of different objects to communicate with each other in dynamic environments. The current trends in VSNs allow different deployment architectures for vehicular networks in highways, urban, and rural environments to support many applications with different QoS requirements. Basically, VSNs came to allow the communication among nearby vehicles as well as fixed roadside equipments which leads to three different configures: vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and, hybrid networks’ architectures as illustrated in Fig. Features of these configurations encounter new challenges in order to expand from being a network of computers to a network of both computers and things. 1 Basic architecture of VSNs, a vehicle-to-vehicle (V2V), b vehicle-to-infrastructure (V2I), c hybrid Devices in the IoT connect with each other using a variety of protocols, and there still exist a large amount of devices that use older communication protocols but have diverse real-time needs. Therefore, VSNs offers integrated communication protocols for effectively monitoring the physical world, especially in urban areas where a high concentration of vehicles equipped with onboard sensors is expected ,. Despite this, integration have benefits such as increasing revenue, reducing costs, and energy efficiency.
However, there exists a serious problem with traffic congestion in decision making for vehicular traffic which is a challenge due to the particular characteristics, such as the highly dynamic topology and the intermittent connectivity. Consequently, VSN has challenges in supporting the real-time traffic information that can significantly improve the safety of the transportation and can reduce the traffic congestion.
This information will help drivers to make smarter decisions in timely manner to prevent accidents, improve the efficiency of the selected route, and provide a safer distance among other vehicles. Therefore, the duty of the embedded sensor is to capture images and measure distance all around a vehicle in order to monitor traffic in an allocated area, while utilizing different devices that can measure several physical traffic parameters. Hence, the view of the vehicle as a sensor platform can improve the traffic flow, via supporting communication with the roadside infrastructure in order to provide ubiquitous coverage. The relative velocities of vehicles are fairly much higher in than 50 km/h in urban environments and more than 100 km/h on the highway. Vehicles also move at different directions. Thus, vehicles can quickly access or leave the network in a very short period of time. This results in more frequent changes in the network topology which affects the network design significantly.
For example, the routing protocol design will be more difficult due to hidden/exposed terminal problem in MAC protocols. Vehicles are typically not affected by strict energy constraints and can be easily equipped with sensor platforms. Meanwhile, VSNs represent a significantly novel and challenging deployment scenario, which considerably differs from the traditional Wireless Sensor Network (WSN) and thus requires innovative solutions in the MAC layer. However, designing an integrated architecture for both WSNs and VSNs often starts with the definition of a MAC protocol since it is a fundamental issue in determining the energy consumption properties and the basic data transport capabilities of the network. This design of an efficient and effective sensory MAC protocol providing QoS requirements for real-time traffic management is considered as the most important step in end-to-end QoS provisioning over VSNs since it regulates nodes’ access to a shared channel and has become a major active research in recent years.
This regulation explicates as duty cycling approach that is considered as one of the primary mechanisms for providing QoS in VSNs. Particularly, duty cycling means that every node in the network is periodically alternating between an awake and a sleep state. Therefore, the duration of a duty cycle is equivalent to the time of an awake state plus the time of sleep state. Whereas the idle state has been founded in IEEE 802.11p standard for vehicular communication that consumes substantial energy to transmit up to 1000 messages with 32 dBm and therefore should be avoided in VSNs. To understand the performance of VSNs and in order to optimize the designed routing protocol , an accurate analytical framework for MAC protocol is required. The main idea of this framework provides an analytical scheme that dynamically adapt the vehicles’ rate of transmission according to their priority.
The analytical model shall describe the effects of assigning various values including the density and transmission range of vehicle to protocol parameter under given specific scenarios in order to achieve the QoS requirements. The remainder of the paper is organized as follows: section discusses some related works devoted entirely to analytical modeling of MAC protocols. Section introduces the synchronous X-MAC protocol, through overview of problem definition of hidden terminal and analyzing power consumption, delay, and network throughput. Section introduces the behavior of X-MAC protocol under specific network conditions through using the proposed Markov model. Meanwhile section introduces the performance analysis of synchronized X-MAC protocol. Furthermore, section introduces detailed simulation and analysis for the performance of a synchronized X-MAC protocol of various scenarios. Finally, section concludes the current.
To better understand the mechanism of a MAC protocol, it is useful to realize that MAC protocols consists usually of three main logical components. First, a collision avoidance (CA) algorithm which uses physical carrier-sensing to register and/or reserve the channel for the duration of the data transmission.
Second, a contention resolution algorithm which uses mechanisms such as back-off to regulate the access to the channel. Third, distributed coordination function (DCF) which is not specifically designed for high mobility network. Various MAC protocols have been proposed to mitigate the adverse effects of hidden terminals through CA, since the hidden problem has demonstrated its energy-saving capabilities. However, in a heterogeneous wireless networks, a hidden problem should be defined as a node out of the range of the sender which covers the receiver. Most CA algorithms are based on sender-initiated, including an exchange of short request-to-send (RTS) and clear-to-send (CTS) messages between a pair of sending and receiving nodes before the transmissions of the actual data packet and the optional acknowledgment packet. Whereas in receiver-initiated, a receiver broadcasts a probing packets whenever it wakes up from sleeping state, while a sender with data packet to transmit waits in the listening state until the probing packets from the receiver is received. Therefore, receiver-initiated MAC protocol degrades the network performance with asymmetric links, due to several experienced sender failures in receiving the probing packets from the receiver.
And hence, the asymmetric links waste energy, increase delay, and degrade the packet receive ratio (PRR). Meanwhile, RTS and CTS message exchange mechanism could not be the solution for VSNs since these exchange messages may not be able to arrive to all hidden nodes. MAC protocols can be divided into two main categories of duty-cycled MAC protocols.
One is synchronized protocols, like S-MAC and T-MAC. The other is asynchronous protocols, like X-MAC and B-MAC. Asynchronous duty-cycled MAC protocols remove the energy overhead for synchronization and are easier to implement as they do not require local synchronization. X-MAC protocol uses data packets as preambles and suits it for sparse networks as the energy and collision increase linearly with the node density. And thus, the performance of X-MAC protocol is evaluated in this work when equipped with CA algorithm to address the performance degradation of wireless multihop communications with hidden terminals, and their impact on MAC protocols. Additionally, the X-MAC contention-based protocol does not perform well in asymmetric scenarios due to the quality of the link from the receiver to the sender which causes the hidden terminal problems and can be avoided if the communication was not receiver-initiated. Many researchers evaluated the performance of various network protocols through simulations.
However, the simulation environment/software is usually too expensive and/or time-consuming, especially while considering a huge network size/capacity. Meanwhile, the analytical models can be more effective in such cases, since the scale of modern networks and the degree of complexity often necessitate the use of simplified assumptions, e.g., Markov, Poisson traffic, or other models. Furthermore, it is hard to capture the dynamic nature of a network without an analytical model; therefore, an analytical model is needed to provide insight into the performance of both routing and MAC protocols. Bianchi proposed an accurate analytical model to analyze the performance of single-hop IEEE 802.11. Ziouva improved Bianchi’s model by adding a deriving saturation delay beside throughput. In an area other than IEEE 802.11 specifically in WSNs the author in proposed a radio model to compute the lower bound of X-MAC protocol.
A new hybrid MAC scheme called Zebra MAC (ZMAC) is proposed in for sensor networks which combine the strengths of TDMA and CSMA while offsetting their weaknesses. The authors in implements an efficient TDMA protocol that apply duty-cycling function for multihop WSNs using semi-Markov chain. Authors tries to avoid channel access problems such as over hearing and hidden terminal by adapting the wakeup/sleep state of each node to the actual operational conditions such as traffic demand and node density.
Short range V2V communication was investigated in. The authors present a study in which effective information such as the message size, transmission range, and velocity of vehicles is exchanged. Such exchanged parameters are considered as factors in analytical model to evaluate the performance of communication. Meanwhile, the authors in presents a study of connectivity in vehicular ad hoc network in traffic free-flow.
Actually, the authors use the analytical model in describing the distribution of distances between the vehicles, traffic flow on the highway to evaluate the effects of various system’s parameters (such as distribution of velocity, traffic flow, and transmission range of vehicles) the network on connectivity. B-MAC considers the default MAC protocol for Mica2 that allows an application to implement its own MAC through a well-defined interface.
To achieve channel utilization and low power operations, the authors adopt low power listening (LPL) and scheduling the clear channel sensing (CCA) technique to reduce duty cycle and to minimize idle listening. Yang in modeled and analyzed the throughput of a synchronized duty-cycle S-MAC protocol for WSNs. S-MAC protocol has different rules for accessing the media as compared against other MAC protocols such as X-MAC or B-MAC.
Yang also proposed a Markov model to analyze the throughput of X-MAC. It should be emphasized that our proposed model is fundamentally different from the one proposed by Yang. Our proposed model analyzes the performance of X-MAC protocol when it is equipped with CA algorithm and aimed of addressing the performance degradation of VSNs with hidden terminal.
However, none included the hidden terminal problem in their analytical models. The paper focuses on the evaluate of an adaptive energy-efficient X-MAC protocol for duty-cycled VSNs.
A Markov queuing model is proposed for modeling the behavior of the X-MAC contention based on the specific sleep/wake-up pattern in the duty cycle. Our proposed model quantifies the desirable QoS metrics for contention-based MAC protocols in multihop fashion to address the hidden terminal problem and to provide fairness in medium sharing among the vehicles. Asynchronous protocols have is promising applications in WSNs since they avoid synchronization overhead, and hence provide higher energy efficiency than synchronized MAC protocols.
Many variations asynchronous duty-cycled MAC protocols have been proposed to improve energy efficiency and packet latency by allowing each node to independently and periodically sleep to save energy. Additionally, asynchronous protocols use a series of short preamble packets to avoid synchronous overheads and hence have higher energy efficiency than synchronized MAC protocols.
These short preamble packets carry the address information of the sink node. As a results the intermediate nodes can go to sleep as soon as they hear the first short preamble. Moreover, the sink can reply with an ACK message in between two successive short preambles to stop the timeline and to start transfering the data packets.
2 The timelines LPL and X-MAC protocol for the short preamble approach X-MAC also has collision related within increasing the network density, i.e., the number of senders increases, and they wake up and begin to send their preamble at the same time since. Thus, all nodes including sink-nodes cannot determine the destination address information in preamble when collision occurs among nodes. In this case, the sender continues sending preambles until next wake-up time. Hence, for each colliding data packet, the average communication of sending data packet is also T. This paper proposes a mathematical model for X-MAC protocol which to includes the effects of CA algorithm.
Our proposed model focuses onto two main contributions which are: (1) solving the problem of medium contention such as hidden or exposed terminal problem, and (2) providing resource reservation for real-time traffic control system in a distributed vehicle-based sensor environment. Moreover, supporting QoS in the routing or transport layer cannot be provided unless the assumption of MAC protocols solves the problems of medium contention and supports reliable communication. Our proposed model acts as analyzer for the performance of X-MAC since the Markov model is used to describe the behavior of accessing of synchronized duty-nodes to the channel. The proposed model elaborates on which type of low duty-cycled MAC protocols should be selected in order to resource the wireless channel reservation that assures the desirable QoS level in real-time traffic control systems.
We propose a Markov model to describe the behavior of X-MAC and investigate the QoS parameters under various network and channel conditions. However, to estimate the effect of the hidden problem, it is necessary to examine the transmission among one-hop neighbor nodes at region where possible hidden problem occurs as depicted in Fig.
In which node A transmits a frame to node B, and node D transmits to node B. Thus, node D will be able to do it, as it is unable to detect the transmission of node A or node C. This means that both nodes C and D are hidden to each other resulting in a collision at node B that causes a serious QoS degradation especially in high-data-rate sensor applications ,.
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In order to satisfy the QoS requirements for real-time traffic control systems, a Markov discrete-time stochastic process M/M/1 queuing model is proposed under realistic conditions for duty cycling with schedule-driven operation in VSNs. We consider a simple traffic model for vehicle moving along a straight road with random velocity. The arrival and departure of the data packets are regulated under a realistic assumption of a finite queue size. Therefore, the proposed model makes the following assumptions:. 1. These assumptions are made based on which have been verified as valid approximations of realistic scenarios. The proposed Markov model shows that the power transition of each sensor node in the network may be modeled by a discrete-time M/M/1 Markov chain, which represents a different predefined status for a node for an event at the wake-up/sleep mode of the duty cycle.
The proposed model considers the following assumptions: (a) The vehicles are equipped with sensor nodes in a network and are assumed to be two-dimensionally Poisson distributed over a domain with density ρ. Therefore, the probability of finding n neighboring nodes in an area S is given by. A node may exchange its status slot by slot, which corresponds to the transition from one state to another in the Markov chain as depicted in Fig. Figure shows that the proposed Markov model has limited queuing capacity denoted as M with finite state slots from left to right, which corresponds to 0 state for processing packets in the queue and so on to m packets in the queue (full queue). Specifically, if a packet arrives and the queue is full, then the packet is simply dropped; nevertheless, the packets are removed from the queue when they are successfully transmitted. By contrast, when the queue is neither full nor empty, then a node may obtain access to the media to transmit packets with an independent probability.
The analysis of the Markov discrete-time M/M/1 queuing model offers insights into the traffic behavior of vehicle-based sensor networks in general and points to an idea for a control algorithm. (7g) If an abnormal event of interest is detected during the specified operations, then Eqs. And describe all transitions from an empty-queue status to a non-empty status according to the Poisson process probability of new packet arrival λ. The typical schedule-driven operation for vehicle-based sensor node operates with two timers: one for the wake-up mode and another for sleep mode, for each node in the network. Therefore, if an abnormal event is detected by a sensor node and needs to be transmitted to another node or to the sink, the node stops the sleep-mode timer, turns on its radio, and starts processing the event; otherwise, the node remains in sleep mode. Equations and describe the transition probability of the schedule-driven duty-cycle node operation, including the processing and transmission of information packets.
Equations and also describe the non-transition probability state (i.e., the probability of having a non-decreasing queue), which can be obtained from two terms depending on the oldest information packets still in the queue and winning the contention to access the media (first term) or otherwise (second term) ,. 4.1 The hidden problem formulation According to the heavy-traffic assumption , each node in the network always has a packet in its buffer to be sent. Suppose a node is ready to transmit with probability p s, the probability of collision is p f, A ı defines the probability that ı of data packet arrives at node during a cycle, and A ≥ ı is the probability that no less than ı data packets arrive at a node during a cycle. Then, p s is considered as a protocol-specific parameter that is slot independent. This means that the probability of transmission and the collision varies from another time slot, depending on the behavior of both duty-cycled node which modeled as Markov-chain and the state of channel which is depicted in Fig., where π 0 indicate the steady state of a node. Because of a node may transmit or not in the slot depending to the mechanism that is used to avoid and resolve the collision as well as the current state of the channel.
Therefore, there is an exact relationship between p s and p f and should be derive to investigate the effects of p s and p f on performance of multihop network.
. Part of the book series (AISC, volume 768) Abstract Wireless sensor networks have been identified as one of the key areas in the field of wireless communication. When an event has occurred, the number of data packets will be generated. A MAC protocol considered for this category of wireless sensor networks, here MAC protocols able to adapt to both light and heavy traffic load situations of the network. Accessible MAC protocols are used for light traffic for the energy efficiency concern. Our proposed systems An Improved Receiver-Centric MAC protocol and Itree-MAC protocol implemented in NS2 Simulator, the significance of this paper is highlight the idle listening, infrequent, and light weight synchronization in wireless sensor networks.
Here evaluating the performance analysis of Improved Receiver-Centric MAC protocol and Itree-MAC protocol; considering comparing parameters like throughput, reliability and end-to-end delay in different sensor nodes in wireless sensor networks. Comparing MAC, receiver-centric MAC, Improved Receiver-Centric MAC with Itree-MAC protocol, the results show that IRC-MAC, Itree-MAC protocols are more efficient than the RC-MAC and IEEE 802.11 MAC protocol. Cite this paper as: Ananda Kumar K.S., Balakrishna R. (2019) Performance Analysis of Reliability and Throughput Using an Improved Receiver—Centric MAC Protocol and Itree-MAC Protocol in Wireless Sensor Networks. In: Mallick P., Balas V., Bhoi A., Zobaa A. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 768.
Springer, Singapore. First Online 12 August 2018.
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