Decomposition Methods for Cross-Layer Optimization in Wireless Networks

A Survey on Cross-Layer Optimization in Wireless Networks

Existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. In this paper, we adopt a deterministic channel model proposed in, a simple abstraction of the physical layer that effectively captures the effect of channel strength, broadcast and superposition in wireless channels. Within the Network Utility Maximization (NUM) framework, we study the cross-layer optimization for wireless networks based on this deterministic channel model. First, we extend the well-applied conflict graph model to capture the flow interactions over the deterministic channels and characterize the feasible rate region. Then we study distributed algorithms for general wireless multi-hop networks. The convergence of algorithms is proved by Lyapunov stability theorem and stochastic approximation method. Further, we show the convergence to the bounded neighborhood of optimal solutions with probability one under constant steps and constant update intervals. Our numerical evaluation validates the analytical results.

The layering principle has been long identified as a way to increase the interoperability and to improve the design of telecommunication protocols, where each layer offers services to adjacent upper layers and requires functionalities from adjacent lower ones. In the past, layering has enabled fast development of interoperable systems, but at the same time limited the performance of the overall architecture, due to the lack of coordination among layers. This issue is particularly relevant for wireless networks, where the very physical nature of the transmission medium introduces several performance limitations for protocols designed for wired networks. To overcome these limitations, a modification of the layering paradigm has been proposed, namely, cross-layer design, or “cross-layering.” Several cross-layering approaches have been proposed in the literature so far. Nevertheless, little formal characterization of the cross-layer interaction among different levels of the protocol stack is available yet. A clear need exists for identifying approaches able to analyze and provide quantitative guidelines for the design of cross-layer solutions, and, more importantly, to decide, in each case, whether cross-layering represents an effective solution or not. This chapter provides a detailed survey of the state-of-the-art and future directions in the usage of formal methods for cross-layer modeling and optimization of wireless networks. The text starts by detailing the principles of layered (ISO/OSI and TCP/IP) protocol stacks as well as the cross-layer paradigm. An overview of the architectures of existing and perspective wireless networks is presented along with an analysis of the potential limitations deriving from the layering approach and detailed description of possible optimization solutions enabled by cross-layer design. Subsequent sections are devoted to the issues of modeling and optimization of wireless networks. The remaining sections cover performance optimization as well as architecture optimization (specifically in terms of signaling). The chapter ends with a summary and outlines about future directions of research on the topic.

Cross-layer optimization for wireless mesh networks with smart antennas

Cyber-Physical System (CPS) is envisioned to tightly integrate the cyber-world of computation, communication, and control with the physical world. CPS is typically designed as a networked system of interacting sensors, actuators, and embedded computing devices to monitor and control the physical world. Thus, one of the essential building blocks of such a system is a highly efficient networking infrastructure. In this paper, we aims to develop an efficient wireless networking technology which can be utilized in CPS. More specifically, we develop a cross-layer optimization model based on the Network Utility Maximization (NUM) framework and its distributed solution for wireless multihop multicast networks exploiting multi-user diversity. It is known that the capacity of a wireless network can be increased by exploiting different channel conditions at different users, i.e., multi-user diversity; however, it is yet to be determined how much performance gain can be achieved by exploiting multi-user diversity in wireless multihop multicast networks. To address this problem, we extend the NUM framework and derive a new optimization problem including the benefits of multi-user diversity for multicasting scenarios in wireless multihop networks under a probabilistic media access control (MAC). In our problem, multi-user diversity is achieved via opportunistic scheduling. Then, we propose a distributed approximation algorithm for the problem. Our numerical results confirm that the benefit of multi-user diversity is prominent in a wireless multihop network with multicast flows.

SummaryDue to the energy scarcity that the wireless sensor networks currently face, many energy‐efficient protocols have been developed and proposed in different layers, especially in the data link and network layers, as a large amount of energy consumed by the transceiver, idle‐listening, collision, selecting the correct nodes to act as routers, long‐distance transmission, etc., which are the responsibility of data link and network layers. Since these protocols address the reasons for energy loss in one layer and neglect the treatment of energy loss in other layers, as each layer of the TCP/IP module has its own features and has no control over the other layers. Therefore, there was a need for a cross‐layer design. In this paper, an energy‐efficient cross‐layer between MAC layer and network layer has been proposed using slotted ALOHA based p‐persistent CSMA MAC protocol and Enhance Energy Conservation based on Residual Energy and Distance (EECRED) in order to reduce energy consumption and increase the network lifetime. The performance of the proposed cross‐layer protocol is evaluated by simulating the protocol using the MATLAB simulation. The simulation results are compared with the Fuzzy and Ant Colony Optimization (ACO) based MAC/Routing cross‐layer protocol (FAMACRO), FAMACRO for wireless sensor networks (FAMACROW), fuzzy cross‐layer LEACH, routing‐MAC, and Energy‐efficient Cross‐layer‐sensing Clustering Method (ECCM) protocols to ensure the efficiency of the proposed cross‐layer. The simulation results show that the proposed cross‐layer protocol is very energy efficient, provides stable networks, consumes little energy, and significantly increases the life of the network compared to the single‐layer protocols where the improvement rate was 45%, 53%, 37%, 91%, and 28.72% compared to FAMACRO, FAMAROW, fuzzy cross‐layer LEACH, routing‐MAC, and ECCM protocols respectively in terms of the number of alive nodes or residual energy.

Video summarization has gained increased popularity in the emerging multimedia communication applications, however, very limited work has been conducted to address the transmission problem of video summary frames. In this paper, we propose a cross-layer optimization framework for delivering video summaries over wireless networks. Within a rate-distortion theoretical framework, the source coding, allowable retransmission, and adaptive modulation and coding have been jointly optimized, which reflects the joint selection of parameters at physical, data link and application layers. The goal is to achieve the best video quality and content coverage of the received summary frames and to meet the delay constraint. The problem is solved using Lagirangian relaxation and dynamic programming. Experimental results indicate the effectiveness and efficiency of the proposed optimization framework, especially when the delay budget imposed by the upper layer applications is small, where more than 10% distortion gain can be achieved.

This paper studies joint scheduling and network coding in wireless multicast networks with independent sources. Designing a network coding solution for wireless networks involves scheduling interference-free transmissions and optimizing a performance measure for the predetermined scheduling sets, followed by constructing network codes for the specific solution. In such a design process, the results of prior steps need to provide enough information to the subsequent steps. In this paper, we formulate a linear optimization problem whose results can be used to design a coding solution. We build our work on previous works and present statistics that show the importance of incorporating unequal timeshares in designing network codes. In particular, our statistics show a throughput improvement of about 35% in maximum flow problems and energy savings between 13% and 30%, depending on the network size, in minimum energy problems. We also present the requirements of code construction algorithms for wireless networks that capture the broadcast property of these networks and can design proper codes when timeshares are unequal. In particular, the adaptation of a centralized network coding scheme for wireless networks is discussed. Overall, the work reported here provides a three-step solution to derive network codes that optimize a performance criterion of interest while also solving the scheduling problem in multihop wireless networks.

In this paper, we propose a detailed energy survey of the physical, data link, and network layer by analytical techniques. We also show the impact of regular sleep periods on node energy consumption and present a comparison analysis of single-hop vs. multi-hop communications in the energy realm. A detailed energy expenditure analysis of not only the physical layer but also the link and network layer provides a basis for developing new energy efficient wireless sensor networks. Regular, coordinated sleeping extends the lifetime of sensor nodes, but systems can only benefit from sleeping in terms of transmitted packets if the data arrival rate to the system is low. Energy efficiency is the driving motivation for it can be considered the most important factor for wireless sensor networks because of the power constraints set by battery operation. Radio solutions in the lower ISM bands are attractive because of their relatively easy implementation and low power consumption. However, the data rates of these commercial radios are also relatively low, limiting transmittable frame sizes to a few tens of octets along with strict duty cycle requirements. From the analysis we extract key parameters of selected MAC protocols and show that some traditional mechanisms, such as binary exponential backoff, have some inherent problems. We also argue that single-hop communications has up todo% lower energy consumption than multi-hop forwarding within the feasible transmission distances of an ISM radio. Index Terms-Energy efficiency, Wireless sensor net- works, Medium access control (MAC) protocols, multi-hop communications a duty cycIe (Z), (3), which is normally 10% for the 434MHz band and 1% for the 868MHz band. The duty cycle is defined as the ratio, expressed as a percentage, of the maximum transmitter on-time, relative to a one hour period. When a sensor network is expected to work continuously, this duty cycle has to be taken into account and it can affect the energy efficiency of a network. In this paper we perform cross-layer analysis by pre- senting topology, medium access control (MAC) and ra- dio transceiver energy consumption models that work in unison. The hear topology model represents a common network after network layer route discovery has been accomplished. We use an energy consumption model for the transmission and reception of MAC frames originally presented in (4), develop a coordinated sleep group energy consumption model, and analytically investigate the effect of sleep on sensor networks using three MAC protocols. From the analysis we show that although in an ideal scenario multi-hop communications perform better than single-hop communications, realistic energy models and especially the MAC protocol design have a significant impact. We propose a multi-group sleep model for our nanoMAC protocol, and show that reg- ular sleep periods have a significant, energy reducing impact on node energy consumption with low traf!fic rates. The radio transceiver energy model takes into account several important radio parameters and we use the RFM TRlOOO and RFM radio designers guide (5) for realistic transceiver parameters. The main metric used is absolute energy, consumption per useful transmitted bit. This means only the MAC or thc network protocol data unit (PDU) will be considered and all the other communicated bits, headers, control frames, preambles, etc. are considered as overhead. The rest of the paper is organized as follows. Some related work is discussed in Section IT and in Section 111 we look at the radio propagation energy model. Section TV presents the network topology and energy

Age of Information (AoI) is an emerging concept to model information freshness from the perspective of destinations of information deliveries. Serving as a metric to characterize the data delivery timeliness, the peak age indicates the maximum value of the AoI prior to a data packet reception. In this paper, we present a distributed scheduling algorithm for peak age optimization in a wireless network where a number of sensor nodes attempt to deliver their sensed data to a data collector over a wireless channel. In particular, each sensor node accesses the channel for data delivery independently according to an adaptively tuned transmission probability. The beauty of our algorithm lies in that, even with neither centralized infrastructure nor coordinations among the sensor nodes, our algorithm asymptotically approximates the optimal solution by only a constant factor. We perform solid theoretical analysis and extensive simulations to verify the efficacy of our algorithm. To the best of our knowledge, it is the first fully distributed scheduling algorithm for AoI optimization in wireless networks.

While terrestrial IoTs have been extensively explored, both academically and commercially, IoUTs have had significantly fewer developments. The underwater channel presents unique challenges which cause commonly utilized communication methodologies in the RF domain to become nonviable. This thesis presents an underwater mesh network designed to address the challenges faced in the network, data link, and physical layers of the underwater acoustic domain. This underwater mesh network implements a proactive routing protocol for maintaining routing topology, allowing for Dijkstra's algorithm to be utilized as an efficient method of determining the next hop for a data packet. Endpoints across an on-board Ethernet socket will be capable of joining the mesh network, allowing for cross-medium data forwarding. A CRC-32 was implemented as the primary methodology for error detection. Two MAC schemes were implemented for this underwater mesh network: a Pure ALOHA scheme and a repetitive burst retransmission scheme. The routing table discovery process and the implemented MAC schemes were evaluated through testing with hardware in a real-world oceanic environment (located in the Boston harbor). Utilizing a ZP-OFDM physical layer, the underwater mesh network's discovery process was able to establish topological consensus on the state of the routing table quickly and accurately in this real-world setting. The repetitive retransmission scheme greatly outperformed the Pure ALOHA scheme due to the greater number of collisions (from acknowledgement packets in the shared channel) in the Pure ALOHA scheme. Through real-world testing, the protocols and systems implemented within this underwater mesh networks were shown to be highly successful at establishing and maintaining a network at varying levels of data traffic. --Author's abstract

Scalable video coding (SVC) and power division multiplexing (PDM) are crucial technologies for video streaming in internet-of-vehicle (IoV) networks due to their robustness over time-varying channels. However, the correlation of video tiers and channel fluctuations induce significant complexity in the joint design of SVC and PDM in IoV networks. To reduce such complexity, we propose a novel transmission strategy for SVC-based video streaming in PDM technology by facilitating cross-layer control across the application, data link, and physical layers. Specifically, we propose a concise framework where the modulation order, the power control, and prioritization of video tiers are jointly controlled. Moreover, we leverage the network abstraction layer units within an arbitrary group-of-pictures to improve the overall video data rate. The formulated joint control of the modulation order, the transmission power, and video-tier prioritization is proved to be a quasi-concave problem. Consequently, our proposed cross-layer optimization based SVC video transmission strategy could efficiently utilize the prioritized video tiers in the application layer, power control in the data-link layer, and modulation orders in the physical layer. Numerical results are used to demonstrate performance improvements over the benchmarks.

This paper deals with the method of how to carry out radio network optimization for 2G and 3G systems with an overview of general GSM radio network optimization areas with regards to analysis and troubleshooting. The general steps and methods for wireless radio network optimization are first addressed. Then optimization methods are introduced. At last the issues of radio network optimization is discussed with special focus on the 2G and 3G networks as well as the required Quality of Service (QoS) to the subscribers. This study would help operators to plan effective optimization of radio resources, enhance coverage, improve quality and increase capacity in future.

In recent times, the application of autonomic soft computing techniques for design and optimization of wireless access networks is progressively becoming prevalent. These computational learning techniques are capable of handling uncertain and imprecise networking information while driving toward the optimal solution set in the problem search space. The approach proposed by this paper presents the application of the fuzzy logic inference combined with the evolutionary genetic algorithm to optimize the performance parameters in wireless networks. In particular, we consider optimal bit rate allocation and transmission power consumption through the joint design of fuzzy-genetic modeling framework. The sample training data generated through simulations of IEEE 802.11 wireless access network are analyzed for optimization by supplying it to the expert hybrid model comprising of the conjunctive design of both the computational intelligent techniques. Specifically, we contemplate the binary encoding scheme, single-point crossover, reversing mutation, and two fitness functions for executing the binary genetic operations of crossover and mutation. It is generally observed that the proposed hybrid model with polynomial fitness function yields better performance with scalable network datasets than the logarithmic fitness function in terms of higher objective value. Moreover, the results obtained through simulation experiments exhibit significant throughput gains and power efficiency for the deployed fitness functions with the evolving size of training dataset. Compared with the existing methods, our hybrid learning model demonstrates performance enhancement with higher expected fitness measure, improved throughput and power efficiency.

WBAN은 인체 내부 및 외부에 부착한 디바이스를 무선으로 연결하여 통신하는 근거리 무선통신 기술로 IEEE 802.15.6 TG BAN을 중심으로 물리, 데이터 링크, 네트워크, 응용계층에서 표준화가 진행되고 있다. WBAN 기술은 전력제한 및 생체특성을 반영하여 센서와 지그비 디바이스를 사용하여 에너지 효율적으로 구성한다. 무선 센서 네트워크는 다수의 센서노드와 센서노드가 전송하는 센싱 데이터를 수집하는 싱크노드로 구성된다. 센서노드는 넓은 지역에 정해진 형태없이 배치되어 프로토콜에 의해 자가구성 능력을 가진다. 본 논문에서는 WBAN 환경에서 적용되고 있는 ZigBee 무선 통신 환경의 주소 지정방식과 라우팅 알고리즘의 성능을 향상시키기 위한 새로운 좌표 값 알고리즘을 제안하였다. 기존 Cskip 알고리즘을 이용한 분산 주소 할당 기법의 낭비되는 주소공간의 문제를 해결하기 위해 (x,y,z) 3개의 좌표 축을 제안하여 16bit 주소공간을 분할하여 사용한다. 각 노드에서 라우팅 시 좌표 값을 이용하여 적은 비트별 연산이 수행되며 멀티 홉을 감소시킬 수 있다. 이에 대한 성능 분석으로 제안한 알고리즘은 수학적 분석 모델을 사용하였고 ZigBee 무선 통신 환경의 계층적 라우팅에서 사용하는 경로 벡터를 사용하여 센서 노드의 멀티 홉 카운트 결과를 도출하였다. 수학적 분석 결과 ZigBee 분산 주소 할당 기법과 기존 알고리즘에 비해 평균 멀티 홉의 수가 감소함으로써 에너지 효율이 향상됨을 입증하였다. The WBAN technology means a short distance wireless network which provides each device interactive communication by connecting devices inside and outside of body. Standardization on the physical layer, data link layer, network layer and application layer is in progress by IEEE 802.15.6 TG BAN. Wireless body area network is usually configured in energy efficient using sensor and zigbee device due to the power limitation and the characteristics of human body. Wireless sensor network consist of sensor field and sink node. Sensor field are composed a lot of sensor node and sink node collect sensing data. Wireless sensor network has capacity of the self constitution by protocol where placed in large area without fixed position. In this paper, we proposed the efficient addressing scheme for improving the performance of routing algorithm by using ZigBee in WBAN environment. A distributed address allocation scheme used an existing algorithm that has wasted in address space. Therefore proposing x, y and z coordinate axes from divided address space of 16 bit to solve this problems. Each node was reduced not only bitwise but also multi hop using the coordinate axes while routing than Cskip algorithm. I compared the performance between the standard and the proposed mechanism through the numerical analysis. Simulation verified performance about decrease averaging multi hop count that compare proposing algorithm and another. The numerical analysis results show that proposed algorithm reduced the multi hop better than ZigBee distributed address assignment