Performance Evaluation and Measurement for Energy Efficient Wireless Networks

Wireless Sensor Networks (WSNs) have emerged as perhaps the most important networking paradigm of recent times, both in terms of their commercial potential and also from a scientific point of view. WSNs are important commercially because of their many applications, spanning from civil to military applications such as structural monitoring of bridges, monitoring of wildlife, tracking of contaminants in the soil and atmosphere. Some of these applications have already proved to be commercially viable and indeed financially very attractive. WSNs are also very important from a scientific point of view, because of their unique features with respect to other types of wireless networks: nodes are typically immobile, and are required to carry a specific type of traffic (which is advantageous), have extreme restrictions on the energy they consume, the processing power they have, and the antennas they can use (which is disadvantageous); in addition, the data created at different sensors may be strongly correlated, which can be beneficial but requires only good algorithms that take advantage of it. Therefore, in the last few years we have experienced an important shift in research activities, moving from general purpose wireless networks to more focused topics specifically on WSNs, taking into account their specific advantages and peculiarities. An important recurring theme in research in this field is the need for energy efficiency, which is the thread of this special issue. The papers which appear in this issue have been carefully selected from the best IEEE PIMRC 2008 conference papers addressing the issue of energy efficiency in WSNs. The respective authors have been asked to provide a significantly extended version of the conference paper, which has subsequently undergone a rigorous review process according to the IJWIN publication standards prior to acceptance. The final set of papers addresses issues at physical, medium access control and networking layers, and to some extent at the application layer. All of these papers take into account the unique peculiarities, advantages, and shortcomings of wireless sensor networks, and propose algorithms and analyses that significantly advance research in the field. We sincerely hope you will enjoy reading them as much as we did. The author of the first paper ‘‘Power Management and Data Rate Maximization in Wireless Energy Harvesting Sensors’’ by Chandra R. Murthy, deals with the problem of power management and throughput maximization for energy neutral operation when using increasingly important but so far rarely analyzed Energy Harvesting Sensors (EHS) to send data over wireless links. The EHS is assumed to be able to harvest energy at a constant rate, and use a fixed part of the energy harvested in a slot for measuring the channel state. The rest of the harvested energy is available for transmission, but it can also be stored in an Wireless Sensor Networks (WSNs) have emerged as perhaps the most important networking paradigm of recent times, both in terms of their commercial potential and also from a scientific point of view. The papers that appear in this issue have been carefully selected from the best IEEE PIMRC 2008 conference papers which addressed the issue of energy efficiency in WSNs. The final set of papers addresses issues at physical, medium access control, networking and to some extend application layers. All of these papers take into account the unique peculiarities, advantages, and shortcomings of wireless sensor networks, and propose algorithms and analyses that significantly advance research in the field. Note that this activity has been partly supported by the NoE-216715 NEWCOM++.

Below the Media Access Control (MAC) layer is the Physical (PHY) layer which deals with the actual transmission of the bits received from the MAC layer above into electromagnetic signals. This layer is optimized to implore power management in wireless networks. Power management is a crucial issue in wireless and mobile networks. In this paper, we propose an Adaptive Context-Aware Rate Selection (ACARS) algorithm to handle the issue of power consumption in wireless networks. This algorithm is implemented by optimizing the PHY layer to transmit efficiently as the number of nodes changes and we estimate the Signal-to-Noise Ratio (SNR) to the PHY layer. Results show that by using the appropriate power management technique, ACARS is reliable and efficient for power consumption in wireless networks which is a high demand for vehicular networks.

Power efficient ultra-wideband based wireless communication for wireless body area network applications

Network coding (NC) is a promising technique recently proposed to improve network performance in terms of maximum throughput, minimum delivery delay, and energy consumption. The original proposal highlighted the advantages of NC for multicast communications in wire-line networks. Recently, network coding has been considered as an efficient approach to improve performance in wireless networks, mainly in terms of data reliability and lower energy consumption, especially for broadcast communications. The basic idea of NC is to remove the typical requirement that different information flows have to be processed and transmitted independently through the network. When NC is applied, intermediate nodes in the network do not simply relay the received packets, but they combine several received packets before transmission. As a consequence, the output flow at a given node is obtained as a linear combination of its input flows. This chapter deals with the application of network coding principle at different communications layers of the protocol stack, specifically, the Medium Access Control (MAC) and physical (PHY) Layers for wireless communication networks.

Optimizing and managing wireless communication network, including improving the utilization of network resources, energy efficiency, automatically carrying out wireless network planning and network construction, is very important to the communication service providers (CSPs). Key performance indicators (KPIs) forecasting for wireless cells, especially the long-term forecasting task, plays a key role in wireless network planning and construction. A new adaptive combination forecasting method is proposed in this paper. The adaptive combination forecasting method has been verified by a real large-scale wireless network dataset which contains thousands of wireless cells and corresponding daily KPIs. After a series steps such as dataset analysis, and Auto-encoder algorithm, K-means algorithm and time series forecasting algorithms, we can obtain the prediction model, then compare its symmetric mean absolute percentage error (SAMPE) value with Holt exponential smoothing, Comb method and Theta method.Experimental results have demonstrated that the proposed method has a better performance, especially in the medium and long term forecasting scenario in terms of symmetric mean absolute percentage error (SMAPE) when compared with some existing methods. It proved that our method can be more suitable for complex wireless communication network environment.

Link quality prediction in mesh networks

This paper presents an ATM based transport architecture for next-generation multiservices personal communication networks (PCN). Such multimedia integrated services wireless networks are motivated by an anticipated demand for wireless extensions to future broadband networks. An ATM based wireless network concept capable of supporting a mix of broadband ISDN services including constant bit-rate (CBR), variable, bit-rate (VBR) and packet data transport is explored from an architectural viewpoint. The proposed system uses a hierarchical ATM switching network for interconnection of PCN microcells, each of which is serviced by high-speed, shared-access radio links based on ATM-compatible cell relay principles. Design issues related to the physical, media access control (MAC) and data link layers of the ATM-based radio link are discussed, and preliminary technical approaches are identified in each case. >

Despite great effort from the research community, wireless networks still operate below full capacity. To increase the network throughput it is important to study algorithms that select communication requests that can decode their signals despite mutual interference. In this paper, we study the joint problem of data rate assignment and link scheduling in the physical interference model. The objective of the problem is to maximize the total number of bits transmitted in one time slot. By constructing an intermediate network representation through a disk graph, we prove that a constant approximation solution can be computed in polynomial time. Finally, we propose a parallel implementation of a polynomial-time approximation scheme and show through simulations that the one-slot throughput of a wireless network can be significantly improved by using variable data rates.

One of the most important types that used to transfer data between nodes without using wires is a “wireless communication network”, where the transmission of data is censored remotely by using electromagnetic waves such as radio waves that usually implemented in the physical layer of the network. Continuous improvements in wireless network technology have reduced the security and speed differences between types of networks (wired and wireless), but in turn, increased security threats to wirelessly transmitted data. Wireless networks are weak in terms of "privacy protection" because anyone who is within the coverage area of a wireless network can attempt to break into that network. Hacking incidents have been reported frequently in places with shared free networks, and it has been observed that the places of open distributed networks of the Internet are most at risk of complete penetration of your phone or PC data. To solve this problem, several programs have been developed that provide protection for wireless networks that differ in terms of security. Some of them did not provide sufficient protection for wireless networks, such as Wired Equivalent Privacy (WEP), and others made progress in preventing intrusions compared to their predecessors, such as Wi-Fi Protected Access (WPA).

This paper presents an initial study on how to model user mobility in a wireless cellular network scenario. The model provides realistic patterns of movement between a number of locations. The aforementioned mobility model is built upon to introduce a base station (BS) energy efficient power state control algorithm (EESC) that is able to provide significant energy savings for the simulated scenario. Erratic subsequent on and off BS behavior is avoided by referring to an average loading curve, generated for each BS during a learning period, when making decisions. Moreover, BSs are turned off only when the users can be handed off to nearby cells with a predefined maximum allowed predicted loss in data rate. The resulting system is able to deliver an energy consumption reduction between 36% and 11% over an always on benchmark for the simulated scenarios. There is negligible loss in terms of achieved data rate per user.

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.

In order to improve the effective ability of sports, it is necessary to carry out sports timing training, construct the wireless communication network of sports timing training, and propose a sports timing training method based on wireless communication. A training model of motion timing in wireless communication network based on spatial interval equilibrium regulation and piecewise load distribution is constructed. The wireless communication transmission channel model of motion timing training is constructed, the channel adaptive equilibrium allocation of motion timing training in wireless communication network is carried out by using spatial equilibrium scheduling method, the orthogonal matching signal tracking model of motion timing training is established. Combined with the load block equilibrium allocation method of multiplex motion timing training, the optimal allocation of motion timing training is carried out. the effectiveness of motion timing training information transmission in wireless communication network is characterized by the number of endpoint paths, and the anti-interference ability of communication is improved by combining the interference suppression method of training environment. The simulation results show that the output quality of motion timing training in wireless communication network is high and the bit error rate (BER) is low, which improves the balanced distribution ability of motion timing training load in wireless communication network.

Wireless Local Area Networks (WLANs) and Wireless Metropolitan Area Networks (WMANs) are two of the main technologies in wireless data networks. WLANs have a short range and aim at providing connectivity to end users. On the other hand, WMANs have a long range and aim at serving as a backbone network and also at serving end users. In this dissertation, we consider the problem of Medium Access Control (MAC) in WLANs and the placement of Relay Stations (RSs) in WMANs. We propose a MAC scheme for WLANs in which stations contend by using jams on the channel. We present analytic and simulation results to find the optimal parameters of the scheme and measure its performance. Our scheme has a low collision rate and delay and a high throughput and fairness performance. Secondly, we present a MAC scheme for the latest generation of WLANs which have very high data rates. In this scheme, we divide the stations into groups and only one station from each group contends to the channel. We also use frame aggregation to reduce the overhead. We present analytic and simulation results which show that our scheme provides a small collision rate and, hence, achieves a high throughput. The results also show that our scheme provides a delay performance that is suitable for real-time applications and also has a high level of fairness. Finally, we consider the problem of placing Relay Stations (RSs) in WMANs. We consider the Worldwide Interoperability for Microwave Access (WIMAX) technology. The RSs are used to increase the capacity of the network and to extend its range. We present an optimization formulation that places RSs in the WiMAX network to serve a number of customers with a pre-defined bit rate. Our solution also provides fault-tolerance by allowing one RS to fail at a given time so that the performance to the users remains at a predictable level. The goal of our solution is to meet the demands of the users, provide fault-tolerance and minimize the number of RSs used.

As the Internet of Things (IoT) continue to advance, the integration of massive devices into wireless networks for communication, sensing, and energy harvesting tasks is becoming increasingly prevalent. This trend has led to the emergence of Integrated Sensing, Communication, and Power Transmission (ISCPT) systems. However, with the proliferation of functionalities within these systems, power consumption has become a critical concern. In this letter we aim to minimize power consumption by optimizing transmit beamforming while ensuring quality of service (QoS), meeting the Cramér–Rao bound (CRB) for radar target sensing accuracy, subject to energy harvesting constraints. To solve the non-convex problem, semidefinite relaxation (SDR) is proposed. Numerical results show that our proposed algorithm can reduce power consumption and satisfy the QoS and CRB constraints.

Aiming at the problems of traditional wireless communication network security vulnerability monitoring systems such as low monitoring accuracy and time-consuming, a machine learning-based intelligent monitoring system for wireless communication network security vulnerabilities is proposed. In the hardware design of the monitoring system, based on the overall architecture of the wireless communication network and the data characteristics of the wireless communication network, it is divided into a vulnerability data collection module, a vulnerability data scanning module, and a network security vulnerability intelligent monitoring module. In the vulnerability data collection module, the wireless data collector is used to collect vulnerability data in the vulnerability database, and according to the attributes of the vulnerability data, the XSS vulnerability detection plug-in is connected to the vulnerability scanner to scan for wireless communication network vulnerabilities; When the communication network vulnerability data signal is traced, the system session operation of monitoring the vulnerability data. The software part introduces the neural network algorithm in the machine learning intelligent algorithm to process the hidden data in the security vulnerability data. The experimental results show that the wireless communication network security vulnerability intelligent monitoring system based on machine learning can effectively improve the system monitoring accuracy and the efficiency of wireless communication network security vulnerability monitoring.