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Here's some useful information. Connect with Ciena Learn more about us. Subscribe now for the latest Network Insights. The Adaptive Network. Analytics and Intelligence. Control and Automation. Programmable Infrastructure. Technology principles. Openness Scalability Security. View all products. Insights by topic. Insights by industry. Get the latest network insights in your inbox Learn more. Contact sales. Mobility implies that nodes can leave and join different parent nodes without affecting the inner functions of the WBAN and avoiding additional energetic resources consumption.
Then, new cross-layer approaches should focus on developing MAC and routing mobility aware schemes. CICADA , for example is a mobility aware scheme but not as robust as WBAN requires, in the case where several sensors disconnect from their parents, the protocol does not seem to nimbly attend to all reconnections, keeping the network in such a state that the whole WBAN could be considered useless. They propose distributing the nodes in two sets, one set comprises the nodes prone to mobility, which run the LIMB protocol to support mobility, and the other set comprises nodes prone to keep static, which run the LIMB protocol and another backbone cross-layer protocol.
Although up to date applications and developments for WBAN have been implemented on existing low data rate and low power existing standards such as IEEE Besides, given the channel variations in the human body, WBANs would experience different phenomena like multipath, fading and shadowing, then a strong physical layer is mandatory. Different traffics are present in WBANs, emergency traffic, on-demand traffic and normal data traffic only for mentioning the most common types, then WBANs should have a strong structure to support traffic differentiation and prioritization while providing a guarantee and reliable service with the lowest latency close to real-time operation ms in medical applications and ms in non-medical applications.
IEEE UWB operates in two frequency bands of The standard suggests WBANs to be deployed in one-hop or two-hops star topologies using a central node performing as hub for the sensor nodes. In IEEE EAP1 and EAP2 access phases are used for emergency traffic, only packets with the highest priority are sent in this phases. Type I access is conveyed in terms of frame time duration while Type II is conveyed in terms of frames count. The length of each division is managed by the central node depending on the application.
Non-beacon mode without superframe boundaries: The access is provided by the central node in unscheduled TypeII polling . In  an energy efficient scheme is based on two-hops transmissions using IEEE The main idea behind the strategy is to reduce the duty cycle of relay nodes and then help to reduce energy consumption. Relay nodes consume more energy as they have to transmit their data and other nodes data as well.
They have to retransmit the downlink from the central node and the uplink from sensor nodes towards central node as well. To reduce the relay nodes duty cycle the central node is allowed to reach directly every node in the network so the downlink does not have to be relayed by intermediate nodes resulting in the reduction of energy consumption by retransmissions, over-hearing and over-heading at relay nodes.
The downlink branch central node-relay node-sensor node is reduced to central node-sensor node while the uplink is kept in its original form. Network lifetime is extended as the relay nodes that were prone to an early exhaustion improve energy consumption by not taking part on the downlink as the standard originally proposes. Basic cross-layer schemes built upon IEEE In  another IEEE This work showed that a compromise between SNR and payload length achieves energy saving in both coded and uncoded transmissions. The aforementioned works show that IEEE Although the standard specification only refers to PHY and MAC layers there is a myriad of possibilities of energy efficient designs starting out from the different PHY layers and access schemes described in the standard.
The design of new protocols and communication schemes for WBAN has to take into consideration issues regarding the physical and medium access layers in both medical and non-medical applications. The majority of cross-layer schemes reviewed in this paper lack of a clear understanding of the limitations and constraints inherent to these layers in WBAN, mainly induced by mobility, channel variations and medical regulations for communications near the human body.
Antenna design: Body composition and characteristics affect the impedance of the antennas. The human body experiences an electromagnetic interaction with the antenna. Regarding the antenna design, designers have to consider body shape, electrical characteristics, non-corrosive materials, radiation patterns and whether the antenna is implanted or not. Aiming to achieve the best performance regarding the tradeoff between energy efficiency and reliability, the designers of MAC protocols for WBAN should take into consideration the mechanisms described in the draft of the IEEE Exploring two parameters, namely, the probability of the channel to stay in good state and the frequency of channel transitions between good state and outage, the designers can devise strategies that can improve the performance without incurring in additional energy consumption.
For example, more efficient mechanisms for dynamic allocation of slots instead of statical or random allocations; adaptive scheduling of retransmissions; effective use of relay nodes in transmissions and schemes for an adaptive control of the transmission power. The scheduling of active and inactive periods in the medium access control still introduces a significant waste of energy by idle listening and overhearing.
Hence a future cross-layer approach should devise a scheme capable of predicting the appropriate length for the wake up and sleep times. Most designs deploy a fixed duty cycle for the sleep frames, and a bad duty cycle choice can result in higher end-to-end latency which could increase dramatically with retransmission which can also result in higher energy consumption to transmit the packets.
The context refers to the environment and the patient conditions where the WBAN is deployed humidity, environment temperature, luminosity, emotions, mental state, stress levels, age and any other extra-information that could help to better characterize the patients situation. In , the authors proposed that context-aware strategies should be implemented over energy-efficient cross-layer approaches between MAC and application layers; they claim that cross-layer in context aware scenarios is needed to address limitations like energy consumption, transmission errors and QoS constraints by an efficient communication of parameters between the MAC layer and the application layer.
They also mention that little research has been done regarding this matter. Unlike regular WSN, WBAN exhibit specific QoS requirements at every single layer: data reliability, traffic segmentation regular data or emergency data , data resolution, bandwidth, path latency, routing maintenance, congestion management, path cost, connectivity robustness, communication range, throughput and transmission reliability .
To fulfill all QoS requirements mentioned above, a regular stack-layered WBAN should increase processing at all layers, and in some cases, increase the transmit power, thus increasing energy consumption. Thus, a cross-layer scheme could help balance the trade-off between QoS and energy consumption.
In almost all of the approaches reviewed, QoS is limited to data-reliability, and in some cases, ignoring that WBAN can manage to provide vital information about a patient's condition. Only in , where the bandwidth is proportionally assigned depending on the variable a sensor is monitoring, so an energy-efficient cross-layer approach should offer the possibility to communicate QoS requirements from one layer to another, especially in medical applications i.
The transmission of vital signs and private data of a patient require the use of mechanisms for data protection and data confidentiality, thus forcing the use of encryption or coding schemes that require extra data processing and hence more energy consumption, so an efficient cross-layer approach for WBAN should fulfill all security requirements and guarantee that the network lifetime will not be affected as well. It is of note mention that none of the papers reviewed in this survey addresses security issues in cross-layer design or in WBAN data management. The authors propose the management of encrypted keys and authentication codes to prevent security issues like packet sniffing or intrusive nodes joining the network, all of this without affecting the power consumption and throughput of the WBAN.
Almost every approach in this survey has been devised under the assumption of an ideal body channel without fading or shadowing effects and the nonstationarity of the channel , and as seen in , on-body channels are hard to characterize, and the best-fit statistical models do not cover all the propagation effects due to diffraction, reflection, fading and absorption of waves in the body channel. We only found a cross-layer scheme taking into account a statistical characterization of body channel: in , an energy-efficient topology aware cross-layer is devised using a close approximation to realistic on-body channel but even this approach only considers LOS transmissions.
In , an stringent analysis of body channels propagation and channel characterization gives insight of various ''myths'' and misconceptions about proper channel modeling, for example, the use of distance based path loss models with fixed path loss exponents for channel characterization. The use of bad shaped distributions to fit both large scale and small scale statistics from data sets gathered in measuring campaigns of body channels and the typecasting of certain body channels as LOS or NLOS not taking into consideration that in most of the situations the body channels are fluctuating between both propagation modes due to body movements.
The goal of this paper is to present a comprehensive survey of the current research works published in the last decade in cross-layer design for energy efficiency in the specific context of wireless body area networks. We focus on recording the most relevant studies that try to solve power consumption issues and the extension of the lifetime of WBAN by the development of novel cross-layer approaches.
From our point of view, most of the works focus on providing new protocols and abstractions to overcome the performance of the classical communication techniques and models. We observe that in nearly almost all the investigations, the authors are not taking mobility into account, and perhaps most of the results obtained in their simulations and implementations could dramatically change when testing their algorithms and protocols in a mobile scenario; we consider this topic to be widely open for future research and to work on it more thoroughly.
We notice that novel cross-layer abstractions aim to replace the traditional stacked model at an early stage because most of the models are based on layer mixtures between adjacent layers or information sharing between pairs of adjacent or non-adjacent layers but still preserving stacked basis. We want to mention that though the existing research on enhancing power consumption in WSN is extensive, most of these approaches were not developed for any specific field e.
We pretend to show the benefits of cross-layer design in the extension of the WBAN lifetime. Although we do not discuss the methods thoroughly, we present them in a very clear and simple way to inspire future research and novel developments. A major issue faced in the review process of cross-layer approaches is that research in this field lacks a ''benchmark'' for a thorough comparison and evaluation of the benefits and shortcomings of such approaches. Thus the evaluation results are not as objective as they should be.
The difficulty in establishing a benchmark lies in the fact that most cross-layer approaches are built and tested under a specific scenario, which in turn, is defined based on the application of interest. Omeni, A. Wai, A. Burdett and C. Circuits and Systems , vol. Marinkovic, C. Spagnol and E. Li and J. Otal, L. Alonso and C. Wireless Comm. Liu, Z.
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Lovelace Binary Sensor
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Sohn, J. Kim and Y. Lee, ''Ieee Lin and P. Movassaghi, M. Regarding the various code caching schemes developed, an uncoded caching scheme [ 9 ] has demonstrated relatively poor caching efficiency, while centralized code caching has demonstrated an index coding problem. Compared to the centralized code caching scheme, decentralized code caching DCC is more flexible, and can adapt to different numbers of user nodes.
In addition, the DCC scheme can alleviate transmission congestion more effectively than the centralized scheme. This paper presents a fundamentally novel cross-layer model based on modifications in the MAC layer and PHY layer to address the low throughput problem and reduce the transmission congestion of WANETs, especially for burst transmission networks.
This scheme also promotes efficient transmission during high traffic periods and makes better use of channels during low traffic periods. The combination of the ContDM scheme with DCC allows the proposed model to solve the unbalanced resource problem by utilizing the characteristics of high and low traffic in networks. The overall transmission process includes two stages: placement stage and delivery stage.
We also offer
The placement stage is initiated when the WANET traffic is low, and the delivery stage occurs when network traffic is high. In this work, we assume that the content request distribution conforms to a Zipfian distribution, which can distinguish between content with high and low frequencies of occurrence [ 10 ]. To briefly describe the Zipfian distribution, we assume a number of elements N , which, in our model, is the number of data packets that must be transmitted at the same time.
The rank of each element is denoted by k and s is the value of the exponent characterizing the distribution. Therefore, the frequency of elements of rank k is obtained as. We employ the Pareto distribution in the proposed model to distinguish between content with high and low frequencies of occurrence. The 80—20 law is widely used in information theory and information transmission. In the placement stage, nodes pre-fetch high-likelihood content from the server, and save the content as cache in their memory. This represents the preparation phase of ContDM transmission.
It is worth noting that the server in the proposed networks acts as a backend database. It does not control or affect the accessing of nodes. All nodes still make up an ad hoc network. The placement stage is regarded as the initialization and setting of the transmission. Here, high-likelihood content is directly sent by the nodes from their cache rather than through the server, which simplifies the transmission process.
Meanwhile, low-likelihood content is still saved on the server, and sent by the server to the nodes when required. The simplified transmission process obtained by the caching of high-likelihood content can improve the transmission performance of WANETs effectively by avoiding traffic congestion in transmission channels among servers. At the first step of the delivery stage, each user node presents requests for its required content. Then, neighboring nodes seek content in their cache and send useful content to the corresponding user nodes according to the ContDM scheme.
The content in its neighbors are pre-fetched in the cache in low traffic period. In ContDM scheme, each neighboring node seeks to divide information into content items and to transmit content to corresponding receiving users, some of which require the same high-likelihood content. This process is illustrated in Fig 1 , where node S is the sender, nodes A, B, C, and E are within the transmission range of S, node D is within the transmission range of B, but not within the transmission range of S.
The cache of S contains n items of high-likelihood content based on the Zipfian distribution. Each content item has an overhead consisting of the location and size of the content. In Fig 1 , S receives requests from neighboring nodes. According to the requests, S sends content 1 to A and C, sends content 2 to D with a hop via B, and sends content 3 to E. Node C only wants content 1, whereas A and D want low-likelihood content from the server.
As a result of the pre-fetch operation involving S, the server can reduce its transmission pressure, and the performance of the network is thereby improved. Therefore, the ContDM scheme enhances WANET efficiency by conducting pre-fetching operations during low traffic periods, and the transmission performance of WANETs is improved during high traffic periods when an increasing number of users require high-likelihood content. In content delivery process of the proposed transmission model, we assume that the sender node S has pre-fetched and cached n content items from the server, some of which are subsequently sent to various receiving nodes A—E.
In the proposed model, we utilize DCC in the transmission process.http://kylemcmakin.com/wp-content/ipoh-hook/wuja-dating-profile-name.php
Cross-Layer Design for the Physical, MAC, and Link Layer in Wireless Systems
These characteristics can help to improve the throughput of the networks. For the example presented in Fig 1 , content 1 requested by A is presented as 2 which is the same as that requested by C. Content items 2 and 3 requested by nodes D via B and E, respectively, are divided similarly as content 1.
We assume that, in this delivery stage, three content items 1, 2, and 3 are required for transmission. Clearly, the content required by D is the same as that required by B, and that of C is the same as A. Therefore, DCC addresses the problem of asynchronous users, and improves the flexibility of networks.
DCC can also improve transmission performance in multi-hop transmission. To illustrate this advantage of DCC, the multi-hop transmission process of the proposed model is presented in detail based on the example shown in Fig 1 , which describes the transmission route from S to D via B. According to the definition given in 1 , we divide the content requested by D into eight sub-contents: 3 In this way, B acts as a relay node in the transmission.