Cross Layer Protocol/Application Design For Wireless Networks

Top PDF Cross Layer Protocol/Application Design For Wireless Networks:

OLSR Protocol with Cross Layer Design In MANET

OLSR Protocol with Cross Layer Design In MANET

This paper shows that For mobile wireless networks The performance of a routing protocol is coupled with factors, like the choice of physical technology ,link layer behavior ,etc The overall behaviour of a protocol specifies its working domain for which it could be suitable .OLSR protocol is proactive or table driven in nature, hence it favors the networking context where this all time-kept information is used more and more .The procotol also goes in favoure of the applications which do not allow long delays in transmitting data packets .OLSR protocol is adapted to the network which is dense, and where the communication is assumed to occur frequently between a large number of nodes.
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A cross layer approach in support of 
		real time data over wireless sensor networks

A cross layer approach in support of real time data over wireless sensor networks

It is well known that wireless sensor devices are very limited in terms of communication and processing capabilities, and storage and energy resources, and that energy is of prime importance. As a result, most algorithms and protocol designs have been made energy efficient. Further, given the characteristics of typical monitoring applications for WSN, a common design practice has been to save energy at the expense of more relaxed QoS performance guarantees, such as low cannel utilization, and longer delays and jitter. For example an approach often used for saving energy has been to design MAC protocols that turn the radios off as much as possible. While this practice saves precious energy, it does it at the expense of worse latency and throughput. Therefore, most of these energy efficient protocols limit the use of WSN to those applications where a prompt response, a delay bounded message delivery, is not important. While this may be a good practice for many applications, there are some applications, such as surveillance and real-time control systems, for which WSN not only need to continue to be energy efficient but also provide better performance.
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A Review on Layered & Cross Layer Design Issues and Security Attacks in Wireless Sensor Networks

A Review on Layered & Cross Layer Design Issues and Security Attacks in Wireless Sensor Networks

The recent researches shown that the layered model is not appropriate for WSNs. So the researchers have made some modification to the protocols which violate the layered approach (OSI Model). In OSI model the layered architecture defines a stack of protocol layers. Here each layer functions within a well defined boundary and perform some well defined functionalities. For implementing a change it is necessary to change the overall system architecture. Layered approach provides modularity, transparency, and standardization in the wired network. But this approach is not suited for WSNs. So we are looking for cross layered communication for enhancing the performance of sensor node. Cross layer design breaks the hierarchical layers of OSI model by merging of layers, implementation of new interfaces and provides additional inter dependencies between any two layers etc. It allows the communication between non adjacent layers of the protocols and sharing of variables between layers. It enables the interaction between different non adjacent layers and exchanging information between layers. The main benefits of cross layer designs include improvement in system performance increased network efficiency and the QOS for different applications .Cross layered design also provide energy efficiency and scalability. This cross layer design is sufficient for both wired and wireless networks. Security Schemes in Wireless Sensor Networks [6-8]
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EECLD:  Energy Efficient Cross Layer Design for Wireless Sensor Networks

EECLD: Energy Efficient Cross Layer Design for Wireless Sensor Networks

[10]-[20]. Munish Gupta et al. [10] has developed a cross layer energy efficient protocol which optimizes energy consumption of the sensor nodes at the Network, MAC and Physical layers of the protocol stack as most of energy consuming factors exist in these three layers, the optimization of energy consumption using cross layer approach is better than the single layer approach. Zeeshan Ali Khan et al. [11] proposed an adaptive routing metric which helps in minimizing the energy consumption as well as meeting the real-time deadlines of the application. Routing metric performs well under different application deadline cases as it takes into account the effect of congestion on a particular path by periodically estimating the delay values. Hui Wang et al. [12] proposed a Decomposition and Combination (D & C) approach to compute the suboptimal solution and also an iterative algorithm is proposed for the D & C approach. The proposed iterative algorithm can also provide a significant improvement on the performance of network lifetime. Morteza Mardani et al. [13] have developed a parallelized distributed algorithm which scales well in the network size and exhibits low computational complexity. Jain-Shing Liu et al. [14] have proposed a cross-layer optimization approach that can seamlessly accommodate routing, scheduling and stream control to simultaneously meet the diverse objectives with the aid of network utility maximization. Cross layer optimization is capable of achieving the joint objective by using the distributed computation. Herman Sahota et al. [15] have designed the MAC Layer to save energy during the wake-up synchronization phase. PD-MAC is more energy efficient than Sensor-MAC (SMAC) for the application. Yong Ding et al. [16] have
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Title :    QOS ORIENTED DISTRIBUTED ROUTING PROTOCOLS FOR HYBRID WIRELESS NETWORKS:AN SURVEY Author (s) : P.NAVEENA

Title : QOS ORIENTED DISTRIBUTED ROUTING PROTOCOLS FOR HYBRID WIRELESS NETWORKS:AN SURVEY Author (s) : P.NAVEENA

Nature of Service provisioning is turning out to be more critical to the achievement of organization of portable adhoc systems (MANETs) for both regular citizen and military applications. QoS design that includes an arrangement of coordinated conventions which empower MANETs with QoS capacity. The conventions will envelop every one of the capacities and calculations expected to ensure QoS at various layers in the systems administration stack, and range from decency ensures in the medium access control layer, to confirmation control in the MAC layer and the Network layer and in addition QoS empowered steering at the system layer. In particular, we will analyze the execution of the adhoc system under the control of this incorporated arrangement of conventions to research the QoS capacity of adhoc systems. This is of fundamental significance as there has not been any work in the field that incorporates every such capacity. To demonstrate the adequacy of the design into giving QoS, a far reaching recreation program has been created that incorporates every one of these conventions, and different situations are reenacted under various activity burdens and versatility designs. In this paper, we discuss the upsides of cross breed remote frameworks including the survey for their creating structures. We discuss the achieving of QoS in remote establishment and MANET. We in like manner discuss about the strategy of achieving QoS in crossbreed Wireless Systems.
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Cross-layer Design and Optimization Techniques in Wireless Multimedia Sensor Networks for Smart Cities

Cross-layer Design and Optimization Techniques in Wireless Multimedia Sensor Networks for Smart Cities

Abstract. The future smart cities vision can be developed through leveraging the potentials of Internet of Things (IoT) and wireless sensor network (WSN) technolo- gies. WSN is a resource constrained network where network nodes are tiny devices that are run on battery power. Diverse types of applications such as environmen- tal and habitual monitoring, detection, and tracking, use WSNs. The invention of new network protocols, the establishment of new models for communications, and testing the available solutions in real world environment are some of the current research issues in WSNs. Main challenges in such networks include energy conser- vation in an efficient way, dealing with variable channel capacity, and the resource constrained nature of such networks. The design of architecture for such networks has a vital role in solving the issues to some extent, i.e., the cross layer design ap- proach is an architectural technique that offers the interaction of different layers to- gether to enhance the performance, minimize the energy consumption, enhance the network life time, and provide Quality of Service (QoS) in real time communica- tions. These are some of the current areas where cross-layer design approaches are being used. This paper presents different types of cross-layer design techniques in wireless multimedia sensor networks. Using such architectural techniques, different state of the art cross-layer optimization approaches are discussed while giving the reader an insight on prominent challenges and issues along with future directions.
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Power Saving Strategies In Wireless Sensor 
                      Networks Using Cross Layer Design

Power Saving Strategies In Wireless Sensor Networks Using Cross Layer Design

Abstract- The latest advances in distributed computing have enabled in the past few years the emergence of a variety of wireless sensor network applications comprising building, health, environment, industry, and military domains. Wireless sensor networks are characterized by constrained power, memory, and computational resources and require a novel design approach. The goal of this thesis is to improve energy performance by employing cross layer design. The goal is achieved by protocol architecture which supports cross layer design and routing protocols which use cross layer information. Energy performance can be enhanced by designing energy aware hardware and software. Energy aware software approach includes development of energy efficient communication protocols and getting benefits from cross layer interaction among layers. In this first, we implement the base station & mobile station. Second, we implement the modulation techniques (OFDM, BPSK, QAM, QPSK) with cyclic prefix values. And lastly, implement the cross layer design. Also we are showing the comparisons using cross layer design & without cross layer design. Simulation result shows the throughput and delay using modulation techniques and cross layer design.
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XL WMSN: cross layer quality of service protocol for wireless multimedia sensor networks

XL WMSN: cross layer quality of service protocol for wireless multimedia sensor networks

Delay at MAC layer can be minimized by using a prioritized scheduling scheme which gives priority to delay intolerant applications. RAP [9] is a communication architecture for sensor networks that proposes velocity- monotonic scheduling in order to minimize deadline miss ratios for packets. Each packet is put to a dif- ferent FIFO queue based on their requested velocity, i.e., the deadline and closeness to the gateway. This ensures prioritization at the MAC layer. In [5-8] tra- ditional layered approach is used to provide different solutions for routing, MAC, and rate control, where each layer provides service only to its adjacent higher layer. This provides modularity and transparency between layers which leads to robust protocol design. However, layered architecture provides a suboptimal solution for WMSNs for two main reasons: (a) limited interaction between adjacent layers through well-defined interfaces, e.g., MAC layer in a layered approach cannot provide channel utilization information to transport layer for rate adjustment and (b) individual processing time per layer increases due to lack of interaction among different layers. Accordingly, cross-layer design has emerged as a promis- ing approach for efficiently meeting multi-constrained requirements of WMSNs. WMSNs by nature have inter- dependence between different layers of the protocol stack. This interdependence can be exploited, through cross- layer cooperation, to guarantee application-specific QoS constraints.
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Cross Layer PHY-MAC Protocol for Wireless Static and Mobile Ad Hoc Networks

Cross Layer PHY-MAC Protocol for Wireless Static and Mobile Ad Hoc Networks

6.3. High Density and Contention Scenario with a Sudden Change of the Contention Level—Heterogeneous Network. We have defined another HD/C scenario (H-D/C scenario 2 in Figure 8), in which a contention level is induced faster than in the previous scenario. The basic access scheme of the DCF is used. The network is heterogeneous, where nodes have an initial energy randomly selected from the range 1–11 Joules. Increases and decreases of the contention level are alternated in short periods of time. These simulations point out the importance of the speed of decrease/increase of the power level. Therefore, we have adjusted the physical parameter ζ of the SNAPdMac protocol in these simulations. Figure 11 shows the total packets received versus the simulation run achieved by the tuned SNAPdMac protocol against the basic power control protocol and IEEE 802.11 DCF standard. We can easily see that the difference between the SNAPdMac protocol performance and other schemes is huge. Comparing both schemes, we can conclude that the SNAPdMac protocol with ζ = 3 can improve the throughput performance around 1.5%, and the FND and lifetime around 3%, however it imposes more loss of routes (where nodes can think that a packet is not received, because a collision occurred somewhere), resulting in a decrease of the throughput fairness around 23% with these simulation settings. This behavior can be explained as follows: because nodes decrease their power level too fast, their signal strength
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Polyhouse Monitoring And Controlling Using Wireless Sensor Network

Polyhouse Monitoring And Controlling Using Wireless Sensor Network

If one of the sub masters fails then the other sub master can also send the data of the other wireless sensor node. The RF(IEEE 806.15.4) module is interfaced to ARM controller. The wireless sensor nodes who are in range receive the incoming frames and stores in the internal RAM memory. If the incoming slave ID matches with their own slave ID then they accept the frame and send the parameter back to the master .If the ID does not match then the slave discards the frame. Wireless sensor nodes will measure the different parameters like temperature, light intensity and Gas and will send back the data to PC master through sub master units. The data will also be displayed on LCD. Relays are provided for controlling action. If the parameters at one of the wireless sensor node are not as per the expected, then the controlling action will be taken by the PC master terminal.
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A robust cross-layer metric for routing protocol in mobile wireless ad hoc networks

A robust cross-layer metric for routing protocol in mobile wireless ad hoc networks

Whereas most existing routing protocols are destination-oriented, DXFP is flow-oriented in that packets are routed taking into account both source and destination. Moreover DXFP is a multipath routing protocol as it maintains multiple paths for the same source-destination flow and chooses to forward the pack- ets of the given flow through the path of minimal cost. Flow-oriented routing has been adopted so as to cope in a better way with the high time variance of the net- work topology and of the link quality. According to the flow-oriented paradigm, whenever a new traffic session is initiated, a Route Discovery procedure is carried out on the basis of the most recent available network informa- tion. Moreover, it must be pointed out that the installation of a path modifies its quality, worsening the congestion of the terminals along the route. Hence, it is of paramount importance, for a correct operation, that each new traffic session probe the network state so as to be routed on the path of minimal delivery delay.
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STUDY ON THE DELAY OF UAV DATA LINK BASED ON DARKROOM CALIBRATE LINK METHOD

STUDY ON THE DELAY OF UAV DATA LINK BASED ON DARKROOM CALIBRATE LINK METHOD

An Energy Optimization Approach based on Cross-Layer for Wireless Sensor Networks named as EOA [15], which consider the joint optimal design of the physical, medium access control (MAC), and routing layer. The focus of EOA is on the computation of optimal transmission power, routing, and duty-cycle schedule that optimize the WSNs energy-efficiency. They have first proposed a feedback algorithm that computes the proper transmission power level between nodes. Then, routing protocol can make use of the transmission power as a metric by choosing route with optimal power consumption to forward packets. Finally, the cross-layer routing information is exploited to form a duty-cycle schedule in MAC layer. EOA is validated on a CROSSBOW’s MicaZ mote platform, and evaluated using the TOSSIM simulator, the simulation results show that EOA is an energy-efficient approach and able to achieve significant performance improvement as well.
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5G Mobile Technology

5G Mobile Technology

The vertical handovers ought not to be utilized, in light of the fact that they are not plausible for some innovations and numerous operators and service providers. The 5G mobile access network grants a service and the 5G network is in- charge of dealing with the mobile users which is the last decision for various wireless networks. These choices will be based on open intelligent middleware in the mobile phone networks. The terminals will access the different wireless technologies. The 5G terminals will have software defined radios which will deliver high bandwidth and lower latency than ever before in mobile networks. The development is seen towards the user terminals as a focus of the 5G mobile networks.
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A Survey: MAC Layer Protocol for Wireless Sensor Networks

A Survey: MAC Layer Protocol for Wireless Sensor Networks

Sensor-MAC (S-MAC) locally managed synchronizations and periodic sleep listen schedules based on these synchronizations form the basic idea behind the Sensor-MAC (S-MAC) protocol [5]. Neighboring nodes form virtual clusters to set up a common sleep schedule. If two neighboring nodes reside in two different virtual clusters, they wake up at listen periods of both clusters. A drawback of S-MAC algorithm is this possibility of following two different schedules, which results in more energy consumption via idle listening and overhearing. Schedule exchanges are accomplished by periodical SYNC packet broadcasts to immediate neighbors. The period for each node to send a SYNC packet is called the synchronization period. Figure 1 represents a sample sender-receiver communication. Collision avoidance is achieved by a carrier sense, which is represented as CS in the figure. Furthermore, RTS/CTS packet exchanges are used for uncast type data packets. An important feature of S-MAC is the concept of message-passing where long messages are divided into frames and sent in a burst. With this technique, one may achieve energy savings by minimizing communication overhead at the expense of unfairness in medium access. Periodic sleep may result in high latency especially for multi-hop routing algorithms, since all immediate nodes have their own sleep schedules. The latency caused by periodic sleeping is called sleep delay in [1]. Adaptive listening technique is proposed to improve the sleep delay, and thus the overall latency. In that technique, the node who overhears its neighbor‟s transmissions wakes up for a short time at the end of the transmission. Hence, if the node is the next- hop node, its neighbor could pass data immediately. The end of the transmissions is known by the duration field of RTS/CTS packets.
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An Enhanced Cross Layer Architecture for Wireless Multihop Networks

An Enhanced Cross Layer Architecture for Wireless Multihop Networks

The operation of XPRESS-TT can be described as follows. EXPRESS establishes the TCP connection between mobile nodes, GWs and MCs. Now mobile nodes send the TCP connection request to the GWs. GWs receives the connection request and placed the entire request in queue. Now XPRESS-TT runs a slotted MAC protocol, where a sequence of slots is organized into frames. For each slot XPRESS selects a set of no interfering links to transmit based on the flow queue lengths and network state. Each node thus maintain queues to store the request and monitors adjacent links to estimate interference and losses.
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Validation of Wireless Sensor Networks with Cross Layer Properties

Validation of Wireless Sensor Networks with Cross Layer Properties

Emerging applications of wireless sensor networks require real-time quality-of-service guarantees to be provided by the network. Because of the nondeterministic impacts of the queuing mechanisms and wireless channel, probabilistic analysis of QoS is essential. A wireless sensor network (WSN) consists of sensor nodes capable of collecting information from the environment and communicating with each other via wireless transceivers. With multi-hop communication the collected data will be delivered to one or more destinations. The sensor nodes are characteristic’s to identify expected to operate with batteries and are often deployed to not-easily-accessible or hostile environment, sometimes in large quantities. To find the optimal communication route from source to destination is only basic and main goal of routing in WSN. Optimal path considers the other network factors as well such as latency, jitter, network originating from above, throughput, communication cost and power in order to communicate between the source and destination without failure.
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Exploiting Symmetric Energy Harvesting Protocol in Wireless Sensor Networks with Outdated Channel State Information: Protocol Design and Performance Analysis

Exploiting Symmetric Energy Harvesting Protocol in Wireless Sensor Networks with Outdated Channel State Information: Protocol Design and Performance Analysis

Abstract: Wireless Powered Communication Networks (WPCN), which has attracted much attention of researchers, also been recently recommended in 5 th generation (5G) wireless networks. With the help of the WPCN, the reliability and battery life of wireless low-power devices can be improved. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward (AF) relaying system, considering two transmission modes including delay-tolerant and delay-limited. As important achievement, we propose symmetric energy harvesting protocol, namely time power switching relaying (TPSR) in order to find maximal throughput. In particular, both time switching and power switching coefficients in this schemes are considered. Unlike most of the previous works, we further focus on impact of outdated channel state information (CSI) in this WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimally harvesting time and power coefficients of the received signal at relay node for energy and information extraction, and by deploying several scenarios. By deploying Monte Carlo simulation, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance, signal-to-noise ratio (SNR) and resulting in other reasonable computations of TPSR need be deployed to obtain QoS requirement.
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Cross layer resource allocation for fault tolerant topology control in wireless mesh networks based on genetic algorithm

Cross layer resource allocation for fault tolerant topology control in wireless mesh networks based on genetic algorithm

As it has been pointed out in [13, 14], the power control in wireless mesh network is NP-complete. This issue is a subset of the topology control problem that has been studied in this paper; therefore, FTTC-TMBF is NP-complete and the computational complexity of FTTC-TMBF increases exponentially with any increase in the network size. In this paper, we propose the Heur- istic FTTC-TMBF (HFTTC-TMBF) method that is composed of four steps. In first step, we suggest an ap- propriate objective function to select the best K disjoint paths between each pair of nodes. This function mini- mizes the number of hops and the consumed power and also takes into account the node utilization balancing. In next step, the Genetic-Based Link Channel Assignment (GB-LCA) algorithm is proposed for assigning channels to links such that potential interference is minimized. In third step, we use the Genetic-Based Compatible Set Formation (GB-CSF) al- gorithm for extracting the set of common-channel links with minimum interference. For this purpose, power control and rate adaptation tools are employed and the cost function is minimized by using the genetic algo- rithm for each compatible set of links. Finally, we intro- duce the Genetic Based Cross Layer Paths Selection (GB-CLPS) algorithm, in which the best paths between each pair of nodes are selected by considering through- put maximization, fairness and balancing on frequency channels and nodes. The proposed algorithms of this paper is implemented in a centralized manner. Since the topology of wireless mesh networks are nearly fixed, the centralized implementation is a proper choice.
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Cross layer design for reducing delay and maximizing lifetime in industrial wireless sensor networks

Cross layer design for reducing delay and maximizing lifetime in industrial wireless sensor networks

There are some similar studies, for example, Chen et al. [56] which studied in a linear network, on how to choose the optimal distance that makes the total energy consumption in the multi-hop network minimum. Obvi- ously, this work is similar to the previous research work; in a linear network, the method of minimizing the energy consumption of a single node can make the total energy consumption of the network minimum, but not necessarily maximize the network lifetime. Simultan- eously, the optimal transmission range of a node is affected by multiple channel parameters; thus, Ref. [57] also shows how to choose optimized channel parameters to reduce the energy consumption. Ref. [58] defines a method known as a Bit-Meter-per-Joule metric to evalu- ate energy efficiency. The authors found the network topology and the nodal density, and the transceiver characteristics affect energy consumption; therefore, optimizing energy consumption needs to be optimized from multiple aspects. Xue Chen et al. [58] consider that minimizing the node energy consumption does not necessarily enable the network to achieve high perform- ance and to maximize the network lifetime is the goal of optimization. This is similar to Yunxia Chen et al. [58] which proposed utilization efficiency which is defined as network lifetime per unit deployment cost. Therefore, the difference between their strategy and previous researches is not to reduce the energy consumption of nodes but to balance the energy consumption of nodes and maximize the network lifetime. Because there is a phenomenon in the sensor network that seriously damages the network lifetime which is called “ energy hole, ” that is, the energy consumption of nodes in the near-sink area is much higher than that in the other areas, these nodes die early and make the entire network prematurely die. And on the other hand, nodes in the far-sink area have a lot of residual energy; therefore, Ref. [49, 50] proposes two approaches to optimize network performance for this situation. The first is a cross-layer optimization method proposed to minimize the energy consumption of transmitting a bit data by selecting the optimal transmit power. Then, selecting the high transmit power for nodes with energy remaining in the far-sink area can effectively improve the data transmis- sion reliability. This strategy improves the reliability of data transmission while maintaining high network lifetime. In addition, the reliability of data transmission is also related to the data transmission distance. If the transmit power of the sender is increased, when the distance between the nodes is far, better transmission efficiency can be maintained but this time will consume
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Cross Layer Design for Cooperative Transmission in Wireless Sensor Networks

Cross Layer Design for Cooperative Transmission in Wireless Sensor Networks

Several protocols and schemes have been proposed to reduce energy consumption in Wireless Sensor Net- works (WSNs). In this paper we employ farcoopt, a cross layer design approach with the concept of cooper- ation among the nodes with best farthest neighbor scheme to increase the Quality of Service (QoS), reduce energy consumption, increases performance and end-to-end throughput. We present cooperative transmission to connect previously disconnect parts of a network thus overcoming the separation problem of multi-hop network. We show that this approach improves connectivity over 50% compared to multi-hop approaches and reduces the number of nodes necessary to provide full coverage of an area up to 35%. Simulation results show that on increase of data rates i.e. packet the network life time increases in farcoopt as compared to tra- ditional multi hop approach. The result of this analysis is presented in this work.
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