Wireless Channel Bandwidth Research Articles

Delay-sensitive task offloading and efficient resource allocation in intelligent edge–cloud environments: A discretized differential evolution-based approach

The number of smart wireless devices (WDs) has enormously increased over the last few years due to the advancement of 5G/B5G networks. The advanced applications of such smart WDs, e.g., augmented reality, virtual reality, online gaming, etc., demand excessive resources. Although the WDs are equipped with limited resources, the evolution of edge computing and offloading techniques enables the WDs to offload their resource-intensive tasks to the nearby edge node. These edge nodes might experience higher loads and delays when WDs generate a huge number of tasks. Moreover, the wireless channel bandwidth and transmission data rate of the wireless channels are also limited. Therefore, optimizing the use of available bandwidth as a valuable resource and reducing latency emerge as crucial objectives while offloading tasks. In this paper, a delay-aware resource-constrained offloading problem for edge–cloud systems is mathematically formulated as a 0–1 integer linear programming, and it is shown to be NP-complete. Then, a delay-aware resource-constrained offloading algorithm based on a discretized differential evolution (DARC-DE) is designed. The objectives of the DARC-DE are to maximize the utilization of the resources as bandwidth and minimize the delay. The vectors are efficiently encoded along with the decoding technique. The fitness function is designed by considering execution, offloading, queuing, transmission delay, and bandwidth utilization. The DARC-DE is shown to be executed in polynomial time. To evaluate DARC-DE, extensive simulation is performed in two different scenarios with varying numbers of tasks and edges. Simulation results demonstrate that the proposed DARC-DE can minimize total delay by 15% to 40% in comparison to particle swarm optimization, genetic algorithm, and bees algorithm, respectively. Simulation results also indicate a significant improvement in bandwidth utilization. Taguchi method and alternative average convergence rate are conducted. The statistical tests—analysis of variance, post-hoc, and Friedman tests—are also performed.

Latency Optimization for Luby Transform Coded Computation in Wireless Networks

Luby transform (LT) code has attracted a significant attention due to its rateless property and low decoding complexity in distributed computing networks. However, for wireless networks, the frequent interaction in LT coded computation can give rise to the latency bottleneck considering the communication overhead of interaction. In this letter, we study a novel LT coded computation scheme for heterogeneous wireless networks. Considering nodes with the disparate computation and transmission capabilities, we propose a block-design based wireless LT coded computation (BD-WLTCC) scheme to balance both computation and transmission latency. First, we pre-allocate the maximum transmission rounds due to the limited bandwidth of wireless channel. Then, we design the sub-block size for each node by formulating a nonconvex optimization problem to avoid the frequent interaction. Finally, the sub-optimal sub-block size is obtained by solving the relaxed problem iteratively. And the optimized results provably reveal the generalization of existing works. Simulation results show the superiority of our scheme.

Offloading dependent tasks in MEC-enabled IoT systems: A preference-based hybrid optimization method

The rapid development of IoT-based services has resulted in an exponential increase in the number of connected smart mobile devices (SMDs). Processing the massive data generated by the large number of SMDs is becoming a big problem for mobile devices, servers, and wireless communication channels. A Multi-access Edge Computing (MEC) paradigm partially mitigates this problem by deploying edge server nodes at the edge of wireless networks nearby SMDs, but the challenge still remains due to the limited computation capacity of MEC servers and the bandwidth of wireless channels. In addition, the dependency of tasks generated by applications on SMDs increases the complexity of the problem. In this paper, we propose a constrained multiobjective computation offloading optimization solution to resolve the problem of task dependency under limited resources. This solution improves the Quality of Service (QoS) through minimizing the latency, energy consumption, and rate of task failure caused by limited resources. We propose a two-staged hybrid computation offloading optimization method to solve the problem. In the first stage, the computation offloading decisions are made based on the preferences of tasks. Then, in the second stage, nearly optimal solutions are found using the modified Non-Dominated Sorting Genetic Algorithm (NSGA-III). The overall efficiency of the proposed method is increased owing to the preference-based algorithm reinforcing the NSGA-III algorithm by generating a better initial population. The results of extensive experiments show that the efficiency of the proposed method is significantly better than the existing methods.

Dynamic Offloading Method for Mobile Edge Computing of Internet of Vehicles Based on Multi-Vehicle Users and Multi-MEC Servers

With the continuous development of intelligent transportation system technology, vehicle users have higher and higher requirements for low latency and high service quality of task computing. The computing offloading technology of mobile edge computing (MEC) has received extensive attention in the Internet of Vehicles (IoV) architecture. However, due to the limited resources of the MEC server, it cannot meet the task requests from multiple vehicle users simultaneously. For this reason, making correct and fast offloading decisions to provide users with a service with low latency, low energy consumption, and low cost is still a considerable challenge. Regarding the issue above, in the IoV environment where vehicle users race, this paper designs a three-layer system task offloading overhead model based on the Edge-Cloud collaboration of multiple vehicle users and multiple MEC servers. To solve the problem of minimizing the total cost of the system performing tasks, an Edge-Cloud collaborative, dynamic computation offloading method (ECDDPG) based on a deep deterministic policy gradient is designed. This method is deployed at the edge service layer to make fast offloading decisions for tasks generated by vehicle users. The simulation results show that the performance is better than the Deep Q-network (DQN) method and the Actor-Critic method regarding reward value and convergence. In the face of the change in wireless channel bandwidth and the number of vehicle users, compared with the basic method strategy, the proposed method has better performance in reducing the total computational cost, computing delay, and energy consumption. At the same time, the computational complexity of the system execution tasks is significantly reduced.

A Review of Approaches for Compassionate Checkpointing with Mobile Computing Systems

A distribution system is a group of autonomous entities working together to address a challenge that cannot be addressed by any one of them alone. A distributed system called a mobile computing device (MCD) has certain processes that are executed on mobile nodes, whose position within the network shifts over time. Distributed mobile systems create new problems such as mobility, poor wireless channel bandwidth, disconnections, low battery life, and a lack of a steady, trustworthy store on mobile nodes. The issue of fault-tolerant computation in mobile distributed databases is discussed in this study. Checkpointing and roll- it-back recovery are the foundations for the procedures outlined.

RETRACTED ARTICLE: Multivariate weighted isotonic regressive modest adaptive boosting-based resource-aware routing in WSN

WSN includes a scenario where many sensor nodes are distributed to monitor environmental conditions with route collected data toward sinks via the internet. WSNs efficiently manage the broader network with available resources, such as residual energy and wireless channel bandwidth. Therefore, a routing algorithm is essential to enhance battery-constrained networks. Many existing techniques are developed for balancing energy consumption, but the efficient routing was not achieved. The multivariate weighted isotonic regressive modest adaptive boosting-based Resource-Aware Routing (MWIRMAB-RAR) technique is introduced to enhance routing. The MWIRMAB-RAR technique includes a different process, namely resource-aware node selection, route path discovery, and data transmission. Initially, the MWIRMAB-RAR technique uses the modest adaptive boosting technique uses the multivariate weighted isotonic regression function for detecting resource-efficient sensor nodes for effective data transmission. After that, multiple route paths are established based on the time of flight method. Once after showing a route path, the source node sends data packets to the sink node via resource-efficient nodes. The data delivery was enhanced and minimized packet loss as well as delay. The simulation analysis is carried out on certain performance factors such as energy consumption, packet delivery ratio, packet loss rate, and delay with several data packets and sensor nodes. The obtained evaluation indicates that MWIRMAB-RAR outperforms well in increasing data packet delivery and reducing energy consumption, packet loss rate, and delay.

Effectual Non-Intrusive Minimum-Process Synchronous Checkpointing Protocol for Mobile Distributed Systems

While dealing with Mobile Distributed systems, we come across some issues like: mobility, low bandwidth of wireless channels and dearth of stable storage on mobile nodes, disconnections, inadequate battery power and high failure rate of mobile nodes. Minimum-process coordinated checkpointing is considered an attractive methodology to introduce fault tolerance in mobile systems transparently. In this paper, we propose a non-blocking coordinated global state compilation algorithm for mobile computing systems, which requires only a minimum number of processes to take permanent recovery points. We reduce the communication complexity as compared to the Cao-Singhal algorithm [4], while keeping the number of useless recovery points unchanged. Finally, the paper presents an optimization technique, which significantly reduces the number of useless recovery points at the cost of minor increase in the communication complexity. In coordinated global state compilation, if a single process fails to take its tentative recovery point; all the recovery point effort is aborted. We try to reduce this effort by taking soft recovery points in the first phase at Mobile Hosts.

A novel arbitration mechanism for crossbar switch in wireless network-on-chip

Wireless network-on-chip (WiNoC) has been introduced as an efficient communication paradigm that can provide high bandwidth and low latency wireless links among long-distance cores. However, the increase of demand for using these shared wireless links and the presence of few numbers of these channels on a chip leads to port contention in WiNoCs. This problem increases the average packet latency as well as the network latency. Therefore, a fair arbitration mechanism is required to eliminate port contention in wireless routers (WRs) and improve the utility of the output port. In this study, we propose a new arbitration mechanism for crossbar switch that can fairly allocate the port priorities based on the current traffic load and the wireless channel bandwidth. The simulation results under synthetic traffic patterns show that the proposed arbitration scheme reduces the average latency and improves the network throughput compared to round robin-based WiNoC.

An Efficient Equal Air-Time Transmission Strategy for Wireless Seismometer Array Based on LoRaWAN With CuckooHash

Recently, large-scale wireless seismometer array (WSA) have played an increasingly important role in oil/gas exploration industry and seismology research. However, due to limited wireless channel bandwidth, transmission latency and high power consumption caused by transmission conflicts in battery-powered seismometers, real-time large-scale WSA system remains unsolved. In this article, we introduce a LoRaWAN-based WSA system with high precise time slot deriving from a synchronization platform composed of GPS timing module and temperature compensated crystal oscillator (TCXO) clock counter. Using the global sharing time slot, we propose an Equal Air Time and CuckooHash (EAT&CH) algorithm for the WSA to resolve channel congestion and delays when multiple seismometers upload data simultaneously. In EAT&CH, an equal air-time spreading factor (SF) allocation method based on the coarse/fine-grained theory is employed to reduce the collision probability of data transmission. To improve the scalability of the WSA in terms of reducing both collision probability and data delay, a different carrier frequency (CF) channel with the same SF allocation plan depending on CuckooHash is designed to reduce the network latency. Simulation results show that the proposed algorithm achieves nearly 100% data extraction rate of the WSA with less than two times the delay, compared with the existing Adaptive Data Rate (ADR) mechanism.

Reliable Through-Metal Wireless Communication Using Magnetic Induction

Wireless sensors or robots in metal-constrained environments leverage through-metal wireless communications to send data and receive instructions. It is well-known that wireless radio frequency (RF) signals cannot penetrate through metal efficiently, which prevents us from applying existing wireless solutions. Moreover, most applications, e.g., metal inspection robots in an oil pipeline, require noncontact wireless communications, where the ultrasonic signals do not work. To this end, we propose to use magnetic induction communication to provide a reliable and flexible solution for wireless sensor and robotic networks in metal-constrained environments. We consider the transceivers are located on two different sides of a metal wall. Then, we develop an analytical model to obtain the optimal configurations of the magnetic coil and the carrier frequency to maximize the communication channel capacity. The received power and wireless channel bandwidth are studied. The results show that the optimal carrier frequency is around 1 kHz. In addition, we study the negative effects caused by coil misalignment and interference, which are circumvented by leveraging a coil array with optimal receiving strategy. The results are evaluated using numerical simulation and verified by finite element method-based simulation.

An adaptive congestion-aware routing algorithm based on network load for wireless routers in wireless network-on-chip

Wireless Network-on-Chip (WiNoC) is regarded as one of the promising alternative approaches for sorting out the issues of latency and power consumption in the conventional Network-on-Chip (NoC). Despite the additional bandwidth of wireless channels on a chip, wireless routers (WRs) are prone to congestion in WiNoC due to the limited number of wireless channels on a chip and the shared use of these channels among all the cores. In this paper, an adaptive congestion-aware routing algorithm consistent with traffic load is proposed for solving the congestion problem of WRs. The proposed algorithm selects source-destination pairs with the longest wired hop distance for using wireless channels. The number of selected packets is determined based on the wireless channel bandwidth and the network traffic load. Simulation results show up to 65% latency improvement, 16% wired/wireless link utilization improvement and a saturation throughput increase of approximately 11%.

Effect of Antenna Shape on Wireless Data Channel Bandwidth in Batteryless Implants

The effect of the shapes of the transmitter and receiver antennas on the voltage gain and the bandwidth of the wireless channel of inductive powering units was evaluated. Antennas with square and round coils were compared. It was shown that under otherwise identical conditions square-coil antennas provided higher voltage gain and broader bandwidth of the wireless channel.

Optimizing Video Transmission for Mobile Devices

As mobile devices that can accommodate multimedia services are increasingly used, video data transmission consumes a significant amount of wireless channel bandwidth. On the other hand, the sizes and resolutions of mobile devices show large variations. In this paper, we investigate the optimal transmission of video data depending on the size and resolution of the mobile devices that include smartphones, tablets and notebooks. A series of subjective tests indicates the bandwidth consumption for multimedia services can be significantly reduced by considering the size and resolution of displays and content characteristics.

Cooperative Change Detection for Voltage Quality Monitoring in Smart Grids

This paper considers the real-time power quality monitoring in power grid systems. The goal is to detect the occurrence of disturbances in the nominal sinusoidal voltage/current signal as quickly as possible such that protection measures can be taken in time. Based on an autoregressive (AR) model for the disturbance, we propose a generalized local likelihood ratio (GLLR) detector which processes meter readings sequentially and alarms as soon as the test statistic exceeds a prescribed threshold. The proposed detector not only reacts to a wide range of disturbances, but also achieves lower detection delay compared to the conventional block processing method. Then we further propose to deploy multiple meters to monitor the power signal cooperatively. The distributed meters communicate wirelessly to a central meter, where the data fusion and detection are performed. In light of the limited bandwidth of wireless channels, we develop a level-triggered sampling scheme, where each meter transmits only one-bit each time asynchronously. The proposed multi-meter scheme features substantially low communication overhead, while its performance is close to that of the ideal case where distributed meter readings are perfectly available at the central meter.

Filtering effects on the synchronization and error performance of promising wireless chaos-based secure communications

Synchronization is one of the most challenging topics involved in the development of promising chaos-based secure communication (CBSC) for wireless applications due its direct impact on the error performance and reliability. In this paper, effects of filtering chaotic signals on the synchronization and average bit-error-rate (BER) of CBSC caused by the limited bandwidth of realistic wireless communication channels and detection requirements are investigated. To overcome the possible drawbacks of filtering process, two efficient methods called chaotic signal reconstruction technique (CSRT) and pre-filtering chaos technique (PFCT) are proposed. The well known double scroll chaotic attractor generated from Chua's circuit is utilized at both transmit and receive nodes as in a drive---response configuration with identical synchronization, and a mathematical model of single-pole low-pass filter is employed in this study. Over Rayleigh fading channel and wide range of filter cut-off frequency (?), simulation results show that as ? decreased, lesser than the bandwidth of utilized chaotic signal, the synchronization mean squared error is increased due to the resulting high distortion in the attractor's ordinary state-space. Consequently, system BER performance is degraded significantly leading to increased possibility of communication link failure. When CSRT from received filtered signal and PFCT of drive chaotic signal are utilized, the achieved results are interesting in terms of robust synchronization and error performance, and provide potential step towards wide adoption of CBSC in future applications.

Learning salient visual word for scalable mobile image retrieval

Owing to the portable and excellent phone camera, people now prefer to take photos and share them in social networks with their friends. If a user wants to obtain relevant information about an image, content based image retrieval method can be utilized. Taking the limited bandwidth and instability of wireless channel into account, in this paper we propose an effective scalable mobile image retrieval approach by exploiting the advantage of mobile end that people usually take multiple photos of an object in different viewpoints and focuses. The proposed algorithm first determines the truly relevant photos according to visual similarity in mobile end, then learns salient visual words by exploring saliency from these relevant images, and finally determines the contribution order of salient visual words to carry out scalable retrieval. Moreover, to improve the retrieval performance, soft spatial verification is proposed to re-rank the results. Compared to the existing approaches of mobile image retrieval, our approach transmits less data and reduces the computational cost of spatial verification. Most importantly, when the bandwidth is limited, we can transmit only a part of features according their contributions to retrieval. Experimental results show the effectiveness of the proposed approach.

Hierarchical Lossless Image Compression for Telemedicine Applications

Abstract The main aim of hierarchical lossless image compression is to improve accuracy, reduce the bit rate and improve the compression efficiency for the storage and transmission of the medical images while maintain an acceptable image quality for diagnosis purpose. The cost and limitation in bandwidth of wireless channels has made compression is necessity in today's era. In medical images, the contextual region is an area which contains an important information and must be transmitted without distortion. In this paper the selected region of the image is encoded with Adaptive Multiwavelet Transform AMWT) using Multi Dimensional Layered Zero Coding (MLZC). Experimental results shows that Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), Mean Structural Similarity Index (MSSIM) performance is high and Root Mean Square Error (RMSE), Mean Absolute Error (MAE) values are low, and moderate Compression Ratio (CR) at high Bits Per Pixel (BPP) when compared to the integer wavelet and multiwavelet transform.

Analysis of the Effect of Coherence Bandwidth on Leakage Suppression Methods for OFDM Channel Estimation

In this paper, we analyze the effect of the coherence bandwidth of wireless channels on leakage suppression methods for discrete Fourier transform (DFT)-based channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Virtual carriers in an OFDM symbol cause orthogonality loss in DFT-based channel estimation, which is referred to as the leakage problem. In order to solve the leakage problem, optimal and suboptimal methods have already been proposed. However, according to our analysis, the performance of these methods highly depends on the coherence bandwidth of wireless channels. If some of the estimated channel frequency responses are placed outside the coherence bandwidth, a channel estimation error occurs and the entire performance worsens in spite of a high signal-to-noise ratio.

Video-Aware Scheduling and Caching in the Radio Access Network

In this paper, we introduce distributed caching of videos at the base stations of the Radio Access Network (RAN) to significantly improve the video capacity and user experience of mobile networks. To ensure effectiveness of the massively distributed but relatively small-sized RAN caches, unlike Internet content delivery networks (CDNs) that can store millions of videos in a relatively few large-sized caches, we propose RAN-aware reactive and proactive caching policies that utilize User Preference Profiles (UPPs) of active users in a cell. Furthermore, we propose video-aware backhaul and wireless channel scheduling techniques that, in conjunction with edge caching, ensure maximizing the number of concurrent video sessions that can be supported by the end-to-end network while satisfying their initial delay requirements and minimize stalling. To evaluate our proposed techniques, we developed a statistical simulation framework using MATLAB and performed extensive simulations under various cache sizes, video popularity and UPP distributions, user dynamics, and wireless channel conditions. Our simulation results show that RAN caches using UPP-based caching policies, together with video-aware backhaul scheduling, can improve capacity by 300% compared to having no RAN caches, and by more than 50% compared to RAN caches using conventional caching policies. The results also demonstrate that using UPP-based RAN caches can significantly improve the probability that video requests experience low initial delays. In networks where the wireless channel bandwidth may be constrained, application of our videoaware wireless channel scheduler results in significantly (up to 250%) higher video capacity with very low stalling probability.

Analysis of Video Coding and Error Resilience Tools of H. 264/AVC in Wireless Environment

Recently more and more telecommunication systems are supporting different kinds of real-time transmission, video transmission being one of the most important application.In wireless environments, channel bandwidth and high packet loss rate are to main limitations in the way of delivering of a good quality video to the end user. Therefore, in applications such as video over wireless networks, a video codec should have ability to handle the erroneous situations of the channels well as the bandwidth limitations.H.264/AVC is the newest international video coding standard, jointly developed by groups from ISO/IEC and ITUT.It has several error resilience techniques to make a video bit stream robust in the erroneous channels conditions and also achieves a significant improvement in the compression efficiency. We analyze various error resilienceschemes and innovative featuresof H.264/AVC for real time video streaming .The focus of the work is to test video coding and error resilience tools of H.264/AVC in real timeenvironment over wireless networks.