Knapsack - TOPSIS Technique for Vertical Handover in Heterogeneous Wireless Network

In a heterogeneous wireless network, handover techniques are designed to facilitate anywhere/anytime service continuity for mobile users. Consistent best-possible access to a network with widely varying network characteristics requires seamless mobility management techniques. Hence, the vertical handover process imposes important technical challenges. Handover decisions are triggered for continuous connectivity of mobile terminals. However, bad network selection and overload conditions in the chosen network can cause fallout in the form of handover failure. In order to maintain the required Quality of Service during the handover process, decision algorithms should incorporate intelligent techniques. In this paper, a new and efficient vertical handover mechanism is implemented using a dynamic programming method from the operation research discipline. This dynamic programming approach, which is integrated with the Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) method, provides the mobile user with the best handover decisions. Moreover, in this proposed handover algorithm a deterministic approach which divides the network into zones is incorporated into the network server in order to derive an optimal solution. The study revealed that this method is found to achieve better performance and QoS support to users and greatly reduce the handover failures when compared to the traditional TOPSIS method. The decision arrived at the zone gateway using this operational research analytical method (known as the dynamic programming knapsack approach together with Technique to Order Preference by Similarity to Ideal Solution) yields remarkably better results in terms of the network performance measures such as throughput and delay.     

Access Point Selection Game with Mobile Users Using Correlated Equilibrium

One of the most important issues in wireless local area network (WLAN) systems with multiple access points (APs) is the AP selection problem. Game theory is a mathematical tool used to analyze the interactions in multiplayer systems and has been applied to various problems in wireless networks. Correlated equilibrium (CE) is one of the powerful game theory solution concepts, which is more general than the Nash equilibrium for analyzing the interactions in multiplayer mixed strategy games. A game-theoretic formulation of the AP selection problem with mobile users is presented using a novel scheme based on a regret-based learning procedure. Through convergence analysis, we show that the joint actions based on the proposed algorithm achieve CE. Simulation results illustrate that the proposed algorithm is effective in a realistic WLAN environment with user mobility and achieves maximum system throughput based on the game-theoretic formulation.     

A self-healing clustering algorithm for underwater sensor networks

Underwater wireless sensor networks (UWSNs) is a novel networking paradigm to explore aqueous environments. The characteristics of mobile UWSNs, such as low communication bandwidth, large propagation delay, floating node mobility, and high error probability, are significantly different from terrestrial wireless sensor networks. Energy-efficient communication protocols are thus urgently demanded in mobile UWSNs. In this paper, we develop a novel clustering algorithm that combines the ideas of energy-efficient cluster-based routing and application-specific data aggregation to achieve good performance in terms of system lifetime, and application-perceived quality. The proposed clustering technique organizes sensor nodes into direction-sensitive clusters, with one node acting as the head of each cluster, in order to fit the unique characteristic of up/down transmission direction in UWSNs. Meanwhile, the concept of self-healing is adopted to avoid excessively frequent re-clustering owing to the disruption of individual clusters. The self-healing mechanism significantly enhances the robustness of clustered UWSNs. The experimental results verify the effectiveness and feasibility of the proposed algorithm.     

IEEE 802.11 Wireless LAN: Saturation Throughput Analysis with Seizing Effect Consideration

The IEEE 802.11 network technology is the emerging standard for wireless LANs and mobile networking. The fundamental access mechanism in the IEEE 802.11 MAC protocol is the Distributed Coordination Function. In this paper, we present an analytical method of estimating the saturation throughput of 802.11 wireless LAN in the assumption of ideal channel conditions. The proposed method generalizes the existing 802.11 LAN models and advances them in order to take the Seizing Effect into consideration. This real-life effect consists in the following: the station that has just completed successfully its transmission has a better chance of winning in the competition and therefore of seizing the channel than other LAN stations. The saturation throughput of 802.11 wireless LANs is investigated by the developed method. The obtained numerical results are validated by simulation and lead to the change of the existing idea of the optimal access strategy in the saturation conditions.     

Proxy based seamless connection management method in mobile cloud computing

Nowadays, complex smartphone applications are developed that support gaming, navigation, video editing, augmented reality, and speech recognition which require considerable computational power and battery lifetime. The cloud computing provides a brand new opportunity for the development of mobile applications. Mobile Hosts (MHs) are provided with data storage and processing services on a cloud computing platform rather than on the MHs. To provide seamless connection and reliable cloud service, we are focused on communication. When the connection to cloud server is increased explosively, each MH connection quality has to be declined. It causes several problems: network delay, retransmission, and so on. In this paper, we propose proxy based architecture to improve link performance for each MH in mobile cloud computing. By proposed proxy, the MH need not keep connection of the cloud server because it just connected one of proxy in the same subnet. And we propose the optimal access network discovery algorithm to optimize bandwidth usage. When the MH changes its point of attachment, proposed discovery algorithm helps to connect the optimal access network for cloud service. By experiment result and analysis, the proposed connection management method has better performance than the 802.11 access method.     

FDTD assessment of human exposure to electromagnetic fields from WiFi and bluetooth devices in some operating situations

In this work, the numerical dosimetry in human exposure to the electromagnetic fields from antennas of wireless devices, such as those of wireless local area networks (WLAN) access points or phone and computer peripherals with Bluetooth antennas, is analyzed with the objective of assessing guidelines compliance. Several geometrical configurations are considered to simulate possible exposure situations of a person to the fields from WLAN or Bluetooth antennas operating at 2400 MHz. The exposure to radiation from two sources of different frequencies when using a 1800 MHz GSM mobile phone connected via Bluetooth with a hands-free car kit is also considered. The finite-difference time-domain (FDTD) method is used to calculate electric and magnetic field values in the vicinity of the antennas and specific absorption rates (SAR) in a high-resolution model of the human head and torso, to be compared with the limits from the guidelines (reference levels and basic restrictions, respectively). Results show that the exposure levels in worst-case situations studied are lower than those obtained when analyzing the exposure to mobile phones, as could be expected because of the low power of the signals and the distance between the human and the antennas, with both field and SAR values being far below the limits established by the guidelines, even when considering the combined exposure to both a GSM and a Bluetooth antenna.     

POTS to broadband ... cable modems

There have been 3 columns talking about broadband communications and now at the very end when it's time to compare using a telco or cableco, I'm asking does it really matter? So what if I can actually get the whole 30 Mbps with a cable network when the website I'm connecting to is running on an ISDN line at 128 Kbps? Broadband offers a lot more bandwidth than the connections many Internet servers have today. Except for the biggest websites, many servers connect to the Internet with a switched 56-Kbps, ISDN, or fractional T1 line. Even with the big websites, my home network only runs a 10 Mbps Ethernet connection to my cable modem. Maybe it doesn't matter that the cable lines are shared or that I can only get 8 Mbps from an ADSL line. Maybe the ISP that I use has a T1 line connection to the Internet so my new ADSL modem has a fatter pipe than my provider! (See table 1). It all makes me wonder what's in store for us in the future. PC technology has increased exponentially in the last 10 years with super fast processor speeds, hard disks of hundreds of gigabytes, and amazing video and audio. Internet connection speeds have failed to keep the same pace. Instead of hundreds of times better or faster--modem speeds are barely 10 times faster. Broadband connections offer some additional speed but still not comparable growth as broadband connections are still in their infancy. Rather than trying to make use of existing communication paths, maybe we need a massive infrastructure makeover of something new. How about national wireless access points so we can connect anywhere, anytime? To use the latest and fastest wireless technology you will simply need to buy another $9.95 WLAN card or download the latest super slick WLAN compression/encryption software. Perhaps it is time for a massive infra-restructuring. Consider the past massive infrastructure efforts. The telcos needed to put in their wiring infrastructure starting in the 1870s before telephones were useful to the masses. CATV was a minor player in the TV broadcast business before they installed their cabling infrastructure and went national. Even automobiles were fairly useless until roads were paved and the highway infrastructure was built!     

Failure-Atomic File Access in the Slice Interposed Network Storage System

This paper presents a recovery protocol for block I/O operations in Slice, a storage system architecture for high-speed LANs incorporating network-attached block storage. The goal of the Slice architecture is to provide a network file service with scalable bandwidth and capacity while preserving compatibility with off-the-shelf clients and file server appliances. The Slice prototype virtualizes the Network File System (NFS) protocol by interposing a request switching filter at the client's interface to the network storage system. The distributed Slice architecture separates functions typically combined in central file servers, introducing new challenges for failure atomicity. This paper presents a protocol for atomic file operations and recovery in the Slice architecture, and related support for reliable file storage using mirrored striping. Experimental results from the Slice prototype show that the protocol has low cost in the common case, allowing the system to deliver client file access bandwidths approaching gigabit-per-second network speeds.     

Task offloading method of edge computing in internet of vehicles based on deep reinforcement learning

Compared with the traditional network tasks, the emerging Internet of Vehicles (IoV) technology has higher requirements for network bandwidth and delay. However, due to the limitation of computing resources and battery capacity of existing mobile devices, it is hard to meet the above requirements. How to complete task offloading and calculation with lower task delay and lower energy consumption is the most important issue. Aiming at the task offloading system of the IoV, this paper considers the situation of multiple MEC servers when modeling, and proposes a dynamic task offloading scheme based on deep reinforcement learning. It improves the traditional Q-Learning algorithm and combines deep learning with reinforcement learning to avoid dimensional disaster in the Q-Learning algorithm. Simulation results show that the proposed algorithm has better performance on delay, energy consumption, and total system overhead under the different number of tasks and wireless channel bandwidth.

     

Metasurface Reflector (MSR) Loading for High Performance Small Microstrip Antenna Design

A meander stripline feed multiband microstrip antenna loaded with metasurface reflector (MSR) structure has been designed, analyzed and constructed that offers the wireless communication services for UHF/microwave RFID and WLAN/WiMAX applications. The proposed MSR assimilated antenna comprises planar straight forward design of circular shaped radiator with horizontal slots on it and 2D metasurface formed by the periodic square metallic element that resembles the behavior of metamaterials. A custom made high dielectric bio-plastic substrate (ε_r = 15) is used for fabricating the prototype of the MSR embedded planar monopole antenna. The details of the design progress through numerical simulations and experimental results are presented and discussed accordingly. The measured impedance bandwidth, radiation patterns and gain of the proposed MSR integrated antenna are compared with the obtained results from numerical simulation, and a good compliance can be observed between them. The investigation shows that utilization of MSR structure has significantly broadened the -10dB impedance bandwidth than the conventional patch antenna: from 540 to 632 MHz (17%), 467 to 606 MHz (29%) and 758 MHz to 1062 MHz (40%) for three distinct operating bands centered at 0.9, 3.5 and 5.5 GHz. Additionally, due to the assimilation of MSR, the overall realized gains have been upgraded to a higher value of 3.62 dBi, 6.09 dBi and 8.6 dBi for lower, middle and upper frequency band respectively. The measured radiation patterns, impedance bandwidths (S11<-10 dB) and gains from the MSR loaded antenna prototype exhibit reasonable characteristics that can satisfy the requirements of UHF/microwave (5.8 GHz) RFID, WiMAX (3.5/5.5 GHz) and WLAN (5.2/5.8 GHz) applications.     

Multi-Parametric Clustering for Sensor Node Coordination in Cognitive Wireless Sensor Networks

The deployment of wireless sensor networks for healthcare applications have been motivated and driven by the increasing demand for real-time monitoring of patients in hospital and large disaster response environments. A major challenge in developing such sensor networks is the need for coordinating a large number of randomly deployed sensor nodes. In this study, we propose a multi-parametric clustering scheme designed to aid in the coordination of sensor nodes within cognitive wireless sensor networks. In the proposed scheme, sensor nodes are clustered together based on similar network behaviour across multiple network parameters, such as channel availability, interference characteristics, and topological characteristics, followed by mechanisms for forming, joining and switching clusters. Extensive performance evaluation is conducted to study the impact on important factors such as clustering overhead, cluster joining estimation error, interference probability, as well as probability of reclustering. Results show that the proposed clustering scheme can be an excellent candidate for use in large scale cognitive wireless sensor network deployments with high dynamics.     

Modeling and Assessing Variability in Energy Consumption During the Use Stage of Online Multimedia Services

In this study, we use an improved, more accurate model to analyze the energy footprint of content downloaded from a major online newspaper by means of various combinations of user devices and access networks. Our results indicate that previous analyses based on average figures for laptops or desktop personal computers predict national and global energy consumption values that are unrealistically high. Additionally, we identify the components that contribute most of the total energy consumption during the use stage of the life cycle of digital services. We find that, depending on the type of user device and access network employed, the data center where the news content originates consumes between 4% and 48% of the total energy consumption when news articles are read and between 2% and 11% when video content is viewed. Similarly, we find that user devices consume between 7% and 90% and 0.7% and 78% for articles and video content, respectively, depending on the type of user device and access network that is employed. Though increasing awareness of the energy consumption by data centers is justified, an analysis of our results shows that for individual users of the online newspaper we studied, energy use by user devices and the third‐generation (3G) mobile network are usually bigger contributors to the service footprint than the datacenters. Analysis of our results also shows that data transfer of video content has a significant energy use on the 3G mobile network, but less so elsewhere. Hence, a strategy of reducing the resolution of video would reduce the energy footprint for individual users who are using mobile devices to access content by the 3G network.     

A mobility-based cluster formation algorithm for wireless mobile ad-hoc networks

In the last decade, numerous efforts have been devoted to design efficient algorithms for clustering the wireless mobile ad-hoc networks (MANET) considering the network mobility characteristics. However, in existing algorithms, it is assumed that the mobility parameters of the networks are fixed, while they are stochastic and vary with time indeed. Therefore, the proposed clustering algorithms do not scale well in realistic MANETs, where the mobility parameters of the hosts freely and randomly change at any time. Finding the optimal solution to the cluster formation problem is incredibly difficult, if we assume that the movement direction and mobility speed of the hosts are random variables. This becomes harder when the probability distribution function of these random variables is assumed to be unknown. In this paper, we propose a learning automata-based weighted cluster formation algorithm called MCFA in which the mobility parameters of the hosts are assumed to be random variables with unknown distributions. In the proposed clustering algorithm, the expected relative mobility of each host with respect to all its neighbors is estimated by sampling its mobility parameters in various epochs. MCFA is a fully distributed algorithm in which each mobile independently chooses the neighboring host with the minimum expected relative mobility as its cluster-head. This is done based solely on the local information each host receives from its neighbors and the hosts need not to be synchronized. The experimental results show the superiority of MCFA over the best existing mobility-based clustering algorithms in terms of the number of clusters, cluster lifetime, reaffiliation rate, and control message overhead.     

A probabilistic neural network approach for modeling and classification of bacterial growth/no-growth data

In this paper, we propose to use probabilistic neural networks (PNNs) for classification of bacterial growth/no-growth data and modeling the probability of growth. The PNN approach combines both Bayes theorem of conditional probability and Parzen's method for estimating the probability density functions of the random variables. Unlike other neural network training paradigms, PNNs are characterized by high training speed and their ability to produce confidence levels for their classification decision. As a practical application of the proposed approach, PNNs were investigated for their ability in classification of growth/no-growth state of a pathogenic Escherichia coli R31 in response to temperature and water activity. A comparison with the most frequently used traditional statistical method based on logistic regression and multilayer feedforward artificial neural network (MFANN) trained by error backpropagation was also carried out. The PNN-based models were found to outperform linear and nonlinear logistic regression and MFANN in both the classification accuracy and ease by which PNN-based models are developed.     

Nest failures in the Scarlet Rosefinch Carpodacus erythrinus

Over a 4-year period nest failures in the Scarlet Rosefinch Carpodacus erythrinus averaged 36.9%. Distance of a nest from a habitat edge was the only factor influencing probability of failure. Predation of incubating females is considered the most likely explanation of the failures.     

Optimizing Network Connectivity for Mobile Health Technologies in sub-Saharan Africa

Background

Mobile health (mHealth) technologies hold incredible promise to improve healthcare delivery in resource-limited settings. Network reliability across large catchment areas can be a major challenge. We performed an analysis of network failure frequency as part of a study of real-time adherence monitoring in rural Uganda. We hypothesized that the addition of short messaging service (SMS+GPRS) to the standard cellular network modality (GPRS) would reduce network disruptions and improve transmission of data.

Methods

Participants were enrolled in a study of real-time adherence monitoring in southwest Uganda. In June 2011, we began using Wisepill devices that transmit data each time the pill bottle is opened. We defined network failures as medication interruptions of >48 hours duration that were transmitted when network connectivity was re-established. During the course of the study, we upgraded devices from GPRS to GPRS+SMS compatibility. We compared network failure rates between GPRS and GPRS+SMS periods and created geospatial maps to graphically demonstrate patterns of connectivity.

Results

One hundred fifty-seven participants met inclusion criteria of seven days of SMS and seven days of SMS+GPRS observation time. Seventy-three percent were female, median age was 40 years (IQR 33–46), 39% reported >1-hour travel time to clinic and 17% had home electricity. One hundred one had GPS coordinates recorded and were included in the geospatial maps. The median number of network failures per person-month for the GPRS and GPRS+SMS modalities were 1.5 (IQR 1.0–2.2) and 0.3 (IQR 0–0.9) respectively, (mean difference 1.2, 95%CI 1.0–1.3, p-value<0.0001). Improvements in network connectivity were notable throughout the region. Study costs increased by approximately $1USD per person-month.

Conclusions

Addition of SMS to standard GPRS cellular network connectivity can significantly reduce network connection failures for mobile health applications in remote areas. Projects depending on mobile health data in resource-limited settings should consider this upgrade to optimize mHealth applications.     

Cost-Effectiveness Analysis of a Mobile Ear Screening and Surveillance Service versus an Outreach Screening,Surveillance and Surgical Service for Indigenous Children in Australia

Indigenous Australians experience a high rate of ear disease and hearing loss, yet they have a lower rate of service access and utilisation compared to their non-Indigenous counterparts. Screening, surveillance and timely access to specialist ear, nose and throat (ENT) services are key components in detecting and preventing the recurrence of ear diseases. To address the low access and utilisation rate by Indigenous Australians, a collaborative, community-based mobile telemedicine-enabled screening and surveillance (MTESS) service was trialled in Cherbourg, the third largest Indigenous community in Queensland, Australia. This paper aims to evaluate the cost-effectiveness of the MTESS service using a lifetime Markov model that compares two options: (i) the Deadly Ears Program alone (current practice involving an outreach ENT surgical service and screening program), and (ii) the Deadly Ears Program supplemented with the MTESS service. Data were obtained from the Deadly Ears Program, a feasibility study of the MTESS service and the literature. Incremental cost-utility ratios were calculated from a societal perspective with both costs (in 2013–14 Australian dollars) and quality-adjusted life years (QALYs) discounted at 5% annually. The model showed that compared with the Deadly Ears Program, the probability of an acceptable cost-utility ratio at a willingness-to-pay threshold of $50,000/QALY was 98% for the MTESS service. This cost effectiveness arises from preventing hearing loss in the Indigenous population and the subsequent reduction in associated costs. Deterministic and probability sensitivity analyses indicated that the model was robust to parameter changes. We concluded that the MTESS service is a cost-effective strategy. It presents an opportunity to resolve major issues confronting Australia’s health system such as the inequitable provision and access to quality healthcare for rural and remotes communities, and for Indigenous Australians. Additionally, it may encourage effective health service delivery at a time when the healthcare funding and workforce capacity are limited.     

Remote data retrieval for bioinformatics applications: an agent migration approach

Some of the approaches have been developed to retrieve data automatically from one or multiple remote biological data sources. However, most of them require researchers to remain online and wait for returned results. The latter not only requires highly available network connection, but also may cause the network overload. Moreover, so far none of the existing approaches has been designed to address the following problems when retrieving the remote data in a mobile network environment: (1) the resources of mobile devices are limited; (2) network connection is relatively of low quality; and (3) mobile users are not always online. To address the aforementioned problems, we integrate an agent migration approach with a multi-agent system to overcome the high latency or limited bandwidth problem by moving their computations to the required resources or services. More importantly, the approach is fit for the mobile computing environments. Presented in this paper are also the system architecture, the migration strategy, as well as the security authentication of agent migration. As a demonstration, the remote data retrieval from GenBank was used to illustrate the feasibility of the proposed approach.     

Performance Enhancement of MC-CDMA System through Novel Sensitive Bit Algorithm Aided Turbo Multi User Detection

Multi carrier code division multiple access (MC-CDMA) system is a promising multi carrier modulation (MCM) technique for high data rate wireless communication over frequency selective fading channels. MC-CDMA system is a combination of code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM). The OFDM parts reduce multipath fading and inter symbol interference (ISI) and the CDMA part increases spectrum utilization. Advantages of this technique are its robustness in case of multipath propagation and improve security with the minimize ISI. Nevertheless, due to the loss of orthogonality at the receiver in a mobile environment, the multiple access interference (MAI) appears. The MAI is one of the factors that degrade the bit error rate (BER) performance of MC-CDMA system. The multiuser detection (MUD) and turbo coding are the two dominant techniques for enhancing the performance of the MC-CDMA systems in terms of BER as a solution of overcome to MAI effects. In this paper a low complexity iterative soft sensitive bits algorithm (SBA) aided logarithmic-Maximum a-Posteriori algorithm (Log MAP) based turbo MUD is proposed. Simulation results show that the proposed method provides better BER performance with low complexity decoding, by mitigating the detrimental effects of MAI.     

A reconfigurable real-time compressive-sampling camera for biological applications

Many applications in biology, such as long-term functional imaging of neural and cardiac systems, require continuous high-speed imaging. This is typically not possible, however, using commercially available systems. The frame rate and the recording time of high-speed cameras are limited by the digitization rate and the capacity of on-camera memory. Further restrictions are often imposed by the limited bandwidth of the data link to the host computer. Even if the system bandwidth is not a limiting factor, continuous high-speed acquisition results in very large volumes of data that are difficult to handle, particularly when real-time analysis is required. In response to this issue many cameras allow a predetermined, rectangular region of interest (ROI) to be sampled, however this approach lacks flexibility and is blind to the image region outside of the ROI. We have addressed this problem by building a camera system using a randomly-addressable CMOS sensor. The camera has a low bandwidth, but is able to capture continuous high-speed images of an arbitrarily defined ROI, using most of the available bandwidth, while simultaneously acquiring low-speed, full frame images using the remaining bandwidth. In addition, the camera is able to use the full-frame information to recalculate the positions of targets and update the high-speed ROIs without interrupting acquisition. In this way the camera is capable of imaging moving targets at high-speed while simultaneously imaging the whole frame at a lower speed. We have used this camera system to monitor the heartbeat and blood cell flow of a water flea (Daphnia) at frame rates in excess of 1500 fps.