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Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting.

Emerging multimedia applications for sensor networks require the co-existence of different types of traffic with different QoS provisions in terms of latency and throughput. Prioritization-based service differentiation mechanisms are applied in all layers of communication to satisfy the QoS requirements of each traffic class. The prioritization in the contention is one of these differentiation methods applied in the medium access layer. In this article, we propose an analytical model for the contention latencies and energy expenditures of different classes in a prioritized contention structure with uniform backoff scheme. The contention window is divided into three partitions which are allocated for the use of only high-priority, both priorities, and only low-priority classes. We further generalize the model for binary exponential backoff schemes and for more than two priority classes. In the analysis, we explore the optimum sizes of these partitions in terms of contention latency and the total energy expenditure for each priority class. Our model is also useful for the evaluation of various recent contention prioritization schemes in WSNs.

Sleeping is an important activity to monitor since it has a crucial role in the overall health and well-being of the people and society. In order to diagnose the problems in sleep, different monitoring systems are developed in the literature. The unobtrusiveness, reduced cost, objectiveness, protection of privacy and user-friendliness are the main design considerations and the proposed system design achieves those objectives by utilizing smart wearables, smart watch and smart phone. The accelerometer and heart rate monitor sensors on smart watch and the sound level sensor on the smart phone are activated. The experiments with this system are performed with 17 subjects in a sleep clinic. The data collected from these subjects is used to generate various combinations by employing varied feature extraction, feature selection and sampling approaches. Five different machine learning algorithms are implemented and the classification results are generated using the various combinations of data, training and scoring strategies. The system performance is measured in two ways, the accuracy rate of distinguishing abnormal respiratory events is 85.95% and the classification success of subjects according to the problems in their respiration is one misclassification among 17 subjects. With all the methodology utilized in this study, the proposed system is a novel prescreening tool which recognizes the severity of problems in respiration during sleep.

Stress has become a significant cause for many diseases in the modern society. Recently, smartphones, smartwatches and smart wrist-bands have become an integral part of our lives and have reached a widespread usage. This raised the question of whether we can detect and prevent stress with smartphones and wearable sensors. In this survey, we will examine the recent works on stress detection in daily life which are using smartphones and wearable devices. Although there are a number of works related to stress detection in controlled laboratory conditions, the number of studies examining stress detection in daily life is limited. We will divide and investigate the works according to used physiological modality and their targeted environment such as office, campus, car and unrestricted daily life conditions. We will also discuss promising techniques, alleviation methods and research challenges.

The release of smart phones equipped with a rich set of sensors has enabled human activity recognition on mobile platforms. Monitoring the daily activities and their levels helps in recognizing the health and wellness of the users as a practical application. Mobile phone’s ubiquity, unobtrusiveness, ease of use, communication channels, and playfulness make mobile phones a suitable platform also for inducing behavior change for a healthier and more active lifestyle. In this paper, we provide a review on the activity recognition systems that use integrated sensors in the mobile phone with a special focus on the systems that target personal health and well-being applications. Initially, we provide background information about the activity recognition process, such as the sensors used, activities targeted, and the steps of activity recognition using machine learning algorithms, before listing the challenges of activity recognition on mobile phones. Next, we focus on the classification of existing work on the topic together with a detailed taxonomy. Finally, we investigate the directions for future research.

The main objective in a wireless sensor network design is to minimize the energy expenditure for sustaining a long lifetime. Moreover, some recent multimedia applications require the network to satisfy specific throughput and delay constraints for large data sizes. In this paper, we analytically derive the expected throughput and the expected energy expenditure for a synchronized contention-based duty cycled MAC protocol. Our analysis explores the combined effect of contention window size, duty cycle and data size on throughput and energy expenditure for a successful transmission. We show that the performance of the network in terms of both metrics fluctuates with increased duty cycle as opposed to the general intuition that an increase in duty cycle increases the throughput and decreases the energy expenditure in the network. The results, validated by simulations, show that in order to provide an efficient MAC operation, the contention window size and the duty cycle should be optimized together for a given data size. (C) 2012 Elsevier B.V. All rights reserved.

Mobile sensing has become a growing area of research in pervasive healthcare. In this paper we present mk-sense, an open framework for mobile sensing on smartphones. mk-sense is an initiative to reduce the efforts of researchers involved in multi-institutional sensing campaign. It is designed to facilitate the collaboration of researchers that run simultaneous data collection efforts in different locations. We illustrate the use of mk-sense with two cross-cultural studies conducted in four different countries (Turkey, Mexico, Switzerland, and Spain) with a total of 77 participants. In this paper, we describe the challenges and experience of conducting research in the wild by using mk-sense as sensing platform. Finally, we present how the conducted studies influenced the design decisions of mk-sense, including features, and tools to monitor data gathering in real-time.

This paper investigated the effects of a paternalistic and empowering leadership style on organizational citizenship behaviour (OCB) in an experimental design using 100 Turkish and 100 Dutch students who held part-time jobs. Confirming our expectations, a paternalistic leadership style had a more positive effect on job dedication and organizational support in Turkey than in the Netherlands. Contradicting our expectations, an empowering leadership style did not have a more positive effect on any of the OCB dimensions in the Netherlands than it did in Turkey. However, in the Netherlands an empowering leadership style had a stronger effect on interpersonal facilitation, job dedication, and organizational support than a paternalistic leadership style. Paternalistic and empowering leadership styles both had positive effects on OCB dimensions in Turkey. As expected, collectivism moderated the relationship between paternalistic leadership style and other oriented OCB (i.e., interpersonal facilitation). Specifically, people who had more collectivistic tendencies were more positively influenced by a paternalistic leader than people who had low collectivistic tendencies in both countries. However, individualism did not have any moderating effects on the relationship between empowering leadership style and self-oriented OCB (i.e., job dedication). Our findings are relevant for understanding the effects of leadership styles and cultural orientations on self- versus other-oriented OCB in Turkey and the Netherlands.

Güney, Evren (Arel Author), Sensors are tiny electronic devices having limited battery energy and capability for sensing, data processing and communicating. They can collectively behave to provide an effective wireless network that monitors a region and transmits the collected information to gateway nodes called sinks. Most of the applications require the operation of the network for long periods of times, which makes the efficient management of the available energy resources an important concern. There are three major issues in the design of sensor networks: sensor deployment or the coverage of the sensing area, sink location, and data routing. In this work, we consider these three design problems within a unified framework and develop two mixed-integer linear programming formulations. They are difficult to solve exactly. However, it is possible to compute good feasible solutions of the sink location and routing problems easily, when the sensors are deployed and their locations in the sensor field become known. Therefore, we propose a tabu search heuristic that tries to identify the best sensor locations satisfying the coverage requirements. The objective value corresponding to each set of sensor locations is calculated by solving the sink location and routing problem. Computational tests carried out on randomly generated test instances indicate that the proposed hybrid approach is both accurate and efficient

Congestion is a challenging problem in wireless sensor networks, which exacerbates with the high volume of data traffic imposed by video applications such as video surveillance and target tracking. Deployment of multiple sinks is a candidate solution for congestion and is also promising in terms of reliability and energy-efficiency. In order to gain the maximum benefit from multiple sinks, it is essential to distribute the load among them evenly. In this paper, we propose a cross layer geographic forwarding scheme MLBRF (Multi-Sink Load Balanced Reliable Forwarding) which aims to provide reliable and energy efficient video delivery in a multi-sinked sensor network for target tracking. In order to provide load balancing among the sinks. MLBRF proposes a sink selection mechanism based on fuzzy logic for the frame forwarding which evaluates the traffic density in the direction of each sink by combining two dynamic criteria which are the number of contenders and the buffer occupancy levels in the neighborhood with the static distance criterion. The performance of the fuzzy sink selection mechanism is compared using simulation with various sink selection mechanisms. The results show that MLBRF gains the maximum benefit from deploying multiple sinks in terms of reliability, latency and energy efficiency by using the proposed fuzzy sink selection mechanism. (C) 2011 Elsevier B.V. All rights reserved.

For wireless sensor networks (WSNs), uneven energy consumption is a major problem. A direct consequence of this is the energy hole problem, formation of sensing voids within the network field due to battery depleted sensors in the corresponding region. Hole formations are inherent in the network topology, yet it is possible to develop strategies to delay the hole formations to later stages of the network operation and essentially extend the network lifetime without sensing quality loss. In this work, we initially propose and analyze an approach that can be used to mitigate the hole problem. The approach is presented in detail and the effects on the sustained surveillance quality are presented. The results are based on simulations with different network configurations with realistic sensor models, MAC and routing protocols. By using the proposed approach, sustaining a sensing quality above a given threshold and more than doubling the network lifetime are possible. The results clearly indicate the suitability of the approach for especially demanding WSNs such as the ones used for border surveillance tasks. (C) 2010 Elsevier Ltd. All rights reserved.

It is a known phenomenon that in a wireless sensor network, sensors communicating directly with a sink deplete their energy faster than the others. As a result, the so-called neighboring sensors can die, disconnecting some of the sinks from the rest of the network, even though most of the sensors are still fully functional. One possible remedy is to balance the relaying load of the sensors using mobile sinks and controlling their mobility, which has attracted the interest of researchers. In this work, we extend the relevant literature by introducing two new mathematical programming models. They intend to maximize the network lifetime through the controlled mobility of a sink with nonzero travel times with and without limiting the number of hops by which the data originating from the sensors reach the sink. Both models allow more than one tour of the sink during the network lifetime and determine the optimal sink route and sojourn times. Since the models are computationally difficult to solve, we propose efficient heuristics methods to compute near-optimal solutions. On the basis of the computational results performed on randomly generated problem instances, we can say that their performance is remarkable.

This study investigated the relationship between employees’ beliefs about their social world (social axioms: reward for application, social cynicism, religiosity, social flexibility, and fate control), their relational identification with their supervisor, and their organizational citizenship behavior (OCB; i.e., interpersonal facilitation, job dedication and organizational support) within collectivistic Turkish society. We expected OCB to depend upon one's relational identification with the supervisor and also to depend on several social axioms, given their salience in collectivistic cultures. We also investigated these relationships across white- and blue-collar workers, as this has not been studied much. To this end, we conducted a survey among 376 Turkish blue-collar and 147 white-collar factory employees. A series of hierarchical regression analyses confirmed our expectations that for both blue- and white-collar workers the reward for application belief was positively related to job dedication and organizational support. Religiosity was positively related to job dedication and organizational support only among blue-collar employees. As hypothesized, relational identification with the supervisor related positively to all dimensions of OCB in blue-collar employees and to interpersonal facilitation and organizational support in white-collar employees. However, the relationship between relational identification with the supervisor and organizational support appeared stronger for blue-collar than for white-collar employees. Apparently, relational identification with the supervisor is an important antecedent of OCB, particularly for blue-collar employees. Theoretical and practical implications of the study findings are discussed.

A wireless sensor network is a network consisting of distributed autonomous electronic devices called sensors. In this work, we develop a mixed-integer linear programming model to maximize the network lifetime by optimally determining locations of sensors and sinks, sensor-to-sink data flows, and activity schedules of the deployed sensors subject to coverage, flow conservation, energy consumption and budget constraints. Since solving this model is difficult except for very small instances, we propose a heuristic method which works on a reformulation of the problem. In the first phase of this heuristic, the linear programming relaxation of the reformulation is solved by column generation. The second phase consists of constructing a feasible solution for the original problem using the columns obtained in the first phase. Computational experiments conducted on a set of test instances indicate that both the accuracy and the efficiency of the proposed heuristic is quite promising. (C) 2010 Elsevier B.V. All rights reserved.

Becoming mature enough to be used for improving the quality of life, wireless sensor network technologies are considered as one of the key research areas in computer science and healthcare application industries. The pervasive healthcare systems provide rich contextual information and alerting mechanisms against odd conditions with continuous monitoring. This minimizes the need for caregivers and helps the chronically ill and elderly to survive an independent life, besides provides quality care for the babies and little children whose both parents have to work. Although having significant benefits, the area has still major challenges which are investigated in this paper. We provide several state of the art examples together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provide a comprehensive analysis of the benefits and challenges of these systems. (C) 2010 Elsevier B.V. All rights reserved.

Edge Computing is a fast growing field of research covering a spectrum of technologies such as Cloudlets, Fog Computing and Mobile Edge Computing (MEC). Edge Computing involves technically more sophisticated setup when compared with the pure Cloud Computing and pure Mobile Computing cases since both computational and network resources should be considered simultaneously. In that respect, it provides a larger design space with many parameters rendering a variety of novel approaches feasible. Given the complexity, Edge Computing designs deserve scientific scrutiny for sound assessment of their feasibility. However, despite increasing research activity, this field lacks a simulation tool compatible with the requirements. Starting from available simulators a significant programming effort is required to obtain a simulation tool meeting the actual needs. To decrease the barriers, a new simulator tool called EdgeCloudSim streamlined for Edge Computing scenarios is proposed in this work. EdgeCloudSim builds upon CloudSim to address the specific demands of Edge Computing research and support necessary functionality in terms of computation and networking abilities. To demonstrate the capabilities of EdgeCloudSim an experiment setup based on different edge architectures is simulated and the effect of the computational and networking system parameters on the results are depicted.

Sensors spend most of their limited battery energy on communicating the collected environmental information to sinks. Therefore, the determination of the optimal sink locations and sensor-to-sink information flow routes becomes important for the survivability of sensor networks. In this work, we address these important design issues using an integrated approach and propose new mixed-integer linear programming models to determine the optimal sink locations and information flow paths between sensors and sinks when sensor locations are given. The first group of proposed models is energy-aware and tries to minimize total routing energy, whereas the second group is financially driven with the objective of minimizing total cost. We do not only report computational results providing information on the solution efficiency of the new formulations, and the accuracy of their linear programming relaxations, but also propose and test new heuristics and lower bounding approaches for the most efficient formulation. (C) 2010 Elsevier B.V. All rights reserved.

For target tracking applications, wireless sensor nodes provide accurate information since they can be deployed and operated near the phenomenon. These sensing devices have the opportunity of collaboration among themselves to improve the target localization and tracking accuracies. An energy-efficient collaborative target tracking paradigm is developed for wireless sensor networks (WSNs). A mutual-information-based sensor selection (MISS) algorithm is adopted for participation in the fusion process. MISS allows the sensor nodes with the highest mutual information about the target state to transmit data so that the energy consumption is reduced while the desired target position estimation accuracy is met. In addition, a novel approach to energy savings in WSNs is devised in the information-controlled transmission power (ICTP) adjustment, where nodes with more information use higher transmission powers than those that are less informative to share their target state information with the neighboring nodes. Simulations demonstrate the performance gains offered by MISS and ICTP in terms of power consumption and target localization accuracy.

In wireless sensor network (WSN) studies, the main objective is minimizing the energy consumption so that the lifetime is maximized under the limited battery capacity constraints. Additionally, in most event-driven WSN applications, the end-to-end delay, and hence, the medium access delay should be minimized. Majority of the WSN MAC protocols are contention-based wherein contention window size setting involves an important trade-off between the collision probability and idle listening durations in contentions where both are aimed to be lowered for efficient network operation. In this paper, the energy optimizing and the delay optimizing contention window sizes are derived as a function of the number of contending nodes. For this purpose, we present separate analyses for the contention delay and for the energy consumed which are verified with detailed simulations. In order to obtain close to optimal performance values in a distributed manner. we propose a method for estimating the number of contending nodes since the individual wireless sensor nodes do not have this information readily. Simulations of an event-driven WSN application verify that the proposed method successfully improve both delay and energy efficiency of the contention-based medium access. The end-to-end network performance is also investigated by employing a geographical routing protocol. Results show that using the heuristic method proposed that use the optimum contention window size analyses presented, the overall network performance can be improved without incurring any overhead to the system. (C) 2009 Elsevier B.V. All rights reserved.

Network lifetime is a novel performance metric which is derived in need to evaluate the networks that are composed of nodes with non-replenishable energy sources. Wireless Sensor Networks (WSNs) are the primary examples of such networks, in which elongating the network lifetime is the main concern. Optimal WSN design is highly dependent on the application scenario context. Correct quantification of the application specific network lifetime is a must to further optimize the design or to comparatively evaluate the proposed schemes - e.g. a legacy layered design vs. a cross-layer implementation. However, in practice, we observe that the focus is given on proposing sophisticated schemes to increase the energy efficiency, whereas only rudimentary lifetime metrics are employed to evaluate the outcome of this effort which compromises the correctness of the results. To realistically and correctly quantify the lifetime, we propose a utility based lifetime measurement framework called Weighted Cumulative Operational Time (WCOT). WCOT lets users incorporate the application dependence into the lifetime metric through its utility based interface. WCOT performs a weighted summation of time where utility values are the weights. With this mechanism, a more representative lifetime metric which maps the complete network behavior into a numeric value is obtained. This is in contrast with metrics which focus solely on certain milestones of the network functionality to quantify the lifetime which include the first node death, the last node death.

We previously proposed a mixed-integer linear-programming formulation, solved by CPLEX, which is a state-of-the-art optimization tool, and two heuristic solutions, layered all-optical multicasting algorithm (LAMA) and conservative fiber and wavelength assignment (C-FWA), for all-optical multicasting in wavelength-routed multifiber wavelength-division multiplexed networks with sparse wavelength conversion and light-splitting restrictions. However, LAMA was not suitable for large and dynamic multicasting problems. In this paper, we evaluate and propose scalable layered all-optical multicasting (SLAM), which is a scalable version of LAMA, for any size static or dynamic multicasting problems. We demonstrate that SLAM performs very close to the optimal (the lower bound/CPLEX) and LAMA, and significantly better than the existing work and C-FWA in terms of nearly all metrics, including the session- and group- blocking probabilities (SBPs and GBPs), since it does not separate routing and fiber-wavelength assignment steps as compared to the other candidates like the existing work and C-FWA. Additionally, transmitter-optimized SLAM, which is a version of SLAM that is specifically tuned to minimize the number of transmitters used, spends three times less extra transmitters than SLAM, without a performance loss in other metrics (one extra transmitter for 12 multicast sessions). Therefore, the adjustable parameters of SLAM make it very flexible to balance different objectives.

Satellite networks are used as backup networks to the terrestrial communication systems. In this work, we tried to find a routing strategy over dynamic satellite systems to better utilize the capacity of the network. The satellite networks are not affected by natural disasters, therefore they can be used widely during and after disasters. The Minimum Flow Maximum Residual (MFMR) routing algorithm over the Routing Set boundaries is proposed in order to better utilize the capacity of the system by distributing the load over the shortest path alternatives of the system. We assumed the satellite network as having finite states and formulated the problem by using Finite State Automation concept along with earth-fixed cell strategy by using a virtual satellite network model. The routing problem in satellite networks is previously studied in the literature and it is conjectured that the problem is NP-Hard. The online and offline problems are stated and the MFMR algorithm is described in detail. The algorithm is compared with alternatives by simulating the network on Opnet Modeler. Finally, the performance analysis of different scenarios is given in this work.

As more complex and distributed applications come into play in today's Internet architecture, the need to have the adequate network architecture to support them with greater speed at lower costs has gained importance. Evolution in the nature of the applications have started to put significant stress on the networks and data centers which have to accommodate the demands of the highly distributed applications. Even though dedicated load balancers for each server can be used, this method is not cost effective and it is vulnerable to congestion and failure. In order to circumvent this problem, dynamic load balancing schemes, which adapt themselves to real-time network traffic, should be adopted. Frequent monitoring of the network traffic allows the load to be distributed fairly over the resources, but since it increases the communication overhead in the network, it deteriorates the system performance in terms of throughput and latency. In this work, our goal is to investigate how fairness and network performance are affected by fine tuning the monitoring and flow rule timeout parameters of an OpenFlow-based dynamic load balancer for data centers which uses real-time network traffic to make traffic-adaptive routing decisions.

This study examined antecedents of organizational citizenship behavior (i.e., reward for application; religiosity beliefs and employees’ relational identification with their supervisor) among Turkish white-collar employees in The Netherlands ( n = 103) and Turkey ( n = 147). OCB related positively to reward for application (both samples) but not to religiosity beliefs among Turkish employees in their home country (Turkey). As expected, relational identification with the supervisor was less strongly related to organizational citizenship behavior among Turkish white-collar employees in their host country (The Netherlands) compared to their home country (Turkey), especially when they resided longer in their host country. Giving increasing globalization and war for talent, findings are relevant to better understand effects of white-collar migrants’ cultural background and acculturation patterns in work-related domains, like OCB.

Thought and Life Logging (Tholilo) is an interdisciplinary research project of computer engineers and psychologists. One aspect of Tholilo is to understand how daily context influence our mood and temporal thinking. In this contribution, we present a data collection framework which records sensor data and survey responses from smartphones to infer user’s context, user’s mood and temporal thinking. In a pilot study, data is collected from two collectives located in Turkey and in Switzerland. We examine correlations between phone data and surveys. As a proof of concept, we show how phone data is correlated with changes in participant’s mood. We conclude with lessons learned and future work.

The purpose of this work is to design a human computer interaction scheme for children in arm rehabilitation therapy. A humanoid robot demonstrates selected arm rehabilitation motions to children. Wearable inertial measurement units (IMUs) are used to monitor children's movements in order to give them proper feedback during therapy and to evaluate their motion performance. Preliminary experiments are done with 5 therapy motions which were selected by physiotherapists. Each motion is related to a goal based functional activity in order to help children to understand and perform the motion easily. Data from children and physiotherapists are recorded and analyzed. It is observed how children accept the robot and the IMUs. Preliminary results show various relationships between therapy motions and specific quaternion axes.

Wireless Information Delivery Environment (WIDE) is a distributed data dissemination system, which uses IEEE 802.11b technology. WIDE aims to deliver popular information services to registered mobile clients in WLAN hot spots. Data delivery is based on broadcasting and multicasting to provide scalability and efficient use of the wireless channel. Reliability is assured with a combination of Forward Error Correction (FEC), data carousel, and ARQ techniques. This paper presents the proposed system architecture with the details of reliable and secure data dissemination mechanisms. Functional evaluation of the proposed system and mechanisms on the implemented prototype are also included in this paper.

Today's handheld computing devices equipped with novel wireless network technologies can provide their users with features such as mobility, multimedia support and group communication. On the other hand, the administrative effort required to enable all these features increases beyond the level that an ordinary user can manage. Ad hoc networks, being able to quickly organise themselves without user intervention, can overcome this problem. They are also suitable for group-oriented mobile multimedia communication. However, it is imperative for ad hoc networks to combine quality of service (QoS) and multicast routing strategies in order to utilise the wireless medium efficiently. This article defines the components of an ad hoc QoS multicast routing (AQM) protocol, which addresses this issue. AQM achieves multicast routing efficiency by tracking the availability of resources for each node within its neighbourhood. Computation of free bandwidth is based on reservations made for ongoing sessions and the allocations reported by neighbours. Current QoS status is announced at the initiation of a new session and updated periodically in the network to the extent of QoS provision. Thus, nodes are prevented from applying for membership if there is no QoS path for the session. When nodes wish to join a session with certain service requirements, a three-phase process consisting of request, reply and reserve steps ensures that the QoS information is updated and used to select the most appropriate routes. The allowed maximum hop count of the session is taken into account in order to satisfy the delay requirements of the multimedia applications. To cope with the continuous nature of streaming multimedia, AQM nodes check the availability of bandwidth within their neighbourhood not only for themselves but within a virtual tunnel of nodes. Objection queries are issued prior to reservation to avoid excessive resource usage due to allocations made by nodes which cannot detect each other directly. New performance metrics are introduced to evaluate the efficiency of AQM regarding the satisfaction level of individual members as well as the success rate of sessions. Simulation results show that, by applying novel QoS management techniques, AQM significantly improves multicast efficiency for members as well as for sessions.

The conceptual shift in the expectations of the wireless users from voice towards multimedia, from availability towards acceptable quality, and from stand-alone towards group-oriented computing has a significant impact on today's networks in terms of the need for mobility, quality of service (QoS) and multicasting. Ad hoc networks, being independent of any fixed infrastructure, can provide mobile users with these features, if necessary QoS multicasting strategies are developed. The aim of this article is to define the building blocks of such an ad hoc QoS multicasting (AQM) protocol. AQM achieves multicasting efficiency by tracking the availability of resources for each node within its neighbourhood. Computation of free bandwidth is based on reservations made for ongoing sessions and similar information reported by neighbours. Current QoS status is announced at the initiation of a new session and updated periodically in the network to the extent of QoS provision. Thus, nodes are prevented from applying for membership if there is no QoS path for the session. When nodes join a session with certain service requirements, a request-reply-reserve process ensures that the QoS information is refreshed and used to select the most appropriate routes. To evaluate the efficiency of AQM in providing multicast users with QoS and satisfying application requirements, two new performance metrics, member and session satisfaction grades are introduced. AQM is compared to a non-QoS scheme with particular emphasis on these criteria. Simulation results show that, by applying QoS restrictions, AQM significantly improves multicasting efficiency. Thus, QoS is both essential for and applicable to multicasting in order to support mobile multimedia applications in ad hoc networks.

Call dropping is considered more annoying than call blocking in wireless cellular networks. The cost of the classical method of employing guard channels to decrease the call dropping rate is the increase in call blocking rate. Since subscriber mobility changes in time, the number of handoff attempts in each cell is subject to fluctuations, making static assignments (or periodical update) of a given number of guard channels inefficient. In this paper, we propose an adaptive scheme that employs reservations, instead of static assignments, to adaptively adjust the number of guard channels in each cell according to the current requirements. Thus, unnecessary allocation of guard channels is avoided resulting in a lower cost in terms of call dropping. The reservation requests are made according to the recent mobility pattern of the subscriber. A likelihood value is associated with each reservation request so that fewer channels are reserved by benefiting from the statistical accumulation of the requests. The channels are reserved by considering the interference that would be created once they are in use. The proposed scheme is evaluated against the classical guard channel scheme with a realistic mobility model.

When wireless sensors are used to keep an area under surveillance, a critical issue is the quality of the deployment from the sensing coverage viewpoint. In this paper, we propose several quality measures, which indicate if the deployment provides sufficient coverage, or whether redeployment is required or not. The terrain is modeled as a grid and the placement of the sensors is uniformly distributed. Neyman–Pearson detection is utilized to determine the effects of false-alarm and signal characteristics on the measures.

In this paper a novel handoff decision algorithm for the mobile subsystem of tactical communications systems is introduced. In this algorithm, handoff decision metrics are: received signal strength measurements from the access points, the ratio of the used capacity to the total capacity for the access points, and relative directions and speeds of the mobiles to the access points. We use a fuzzy inference system to process these metrics. We also introduce a "membership value" to represent the degree of membership of a mobile to an access point and "membership value threshold" to represent the minimum membership value before a mobile considers handing off to another access point. We compare our algorithm with the received-signal strength-based handoff decision algorithms. Our tests have shown that the proposed scheme, with the lowest membership value threshold, achieves the minimum number of handoffs, and the proposed scheme with the highest membership value threshold achieves the minimum call blocking rate.

textabstractThe present study aimed to investigate Turkish university youth’s constructions concerning the European Union (EU) and their reactions to the EU’s December 2002 Copenhagen summit decision to delay discussion of Turkey’s entry to the EU. Specifically it aimed to show that socio-political identities among Turkish youth were related to historical developments in Turkey’s past and that these identities had associations with values of ethnocentricism, patriotism, and secularism. Furthermore it was predicted that constructions of the EU reactions to the decision would be related. Students (400) from five universities at the three largest cities of Turkey participated in the study. Three identities, Nationalist-Islam, Kemalist, and Western; three constructions of the EU, Europe as Different, Impermeable Boundaries, and Different but Advantageous, and two perceived causes for the decision, Differences-Conflict and Justification emerged from factor analyses. Second order factor analysis revealed that Nationalist-Islam identity and authoritarian, ethnocentric and antisecular values formed a cluster whereas Kemalist and Western identities were grouped with low levels of patriotism. Positive and negative constructions of the EU and reactions to the Copenhagen decision were also grouped under two separate factors. Further analyses revealed that an index of urbanization composed of parental education and rural-urban origin predicted the Authoritarian-Nationalistic cluster and that this value-identity cluster predicted positive and negative views of the EU.

The validity of the mobility model used to evaluate a cellular network determines the validity of the evaluation. In the literature, unrealistic assumptions on mobility are exercised for the sake of simplicity. In this paper, we present a novel mobility model which is realistic in the sense that it captures the moving-in-groups, conscious traveling and inertial behaviours of the subscribers while respecting the non-pass-through feature of structures like households and preserving the autonomy of the subscribers. The mobility and call patterns of the subscribers are determined according to the locus of the subscriber over a real map. Thus, our model allows the subscribers to leave home or arrive home, walk or drive in the streets, get on the highways at specific entry points together with numerous hot and blind spots in the terrain, like city centers and lakes. The call pattern of a subscriber is affected by the type of structure he is in. The model can work on real maps to simulate the mobility patterns in real life. We have evaluated the proposed model against the well-known way point mobility model. We also analyzed the effect of the mobility model on systems with and without guard channels. Copyright © 2004 John Wiley & Sons, Ltd.

In this article, a rapidly deployable PCS architecture based on our novel resource management scheme, namely, virtual cell layout (VCL), is introduced. VCL is used to develop new self-organization and routing procedures that mitigate the scalability problem of infrastructureless routing and resource management. In VCL, the communication area is tessellated with regularly shaped fixed-size virtual cells. Radio resources such as frequency carriers and CDMA codes are assigned to the fixed cells of this layout. The real cells, which do not need to be the some size as the virtual cells, can move over the VCL cells. Simulation results show that the VCL-based architecture satisfies the requirement for rapid deployment and can provide an acceptable grade of service.

A new scheme for the simulation of tactical communications systems is introduced in which the mobility, call, and availability patterns for communications equipment are generated by using the data inferred from joint theater-level battle simulations. In this technique, the mobility, strength, and posture data related to military units are stored in a database by a military constructive simulation system during computer-aided exercises. Then, the mobility, call, and availability patterns for the communications equipment are derived from these data in the required detail and time resolution by the authors' models. The data structures and the statistical data used in these models, the description of a tactical communications system studied by using the authors' technique, and example results from this study are also presented.

Due to the scarcity of the spectral resources and mobility of the portables, the call attempts may be blocked during call initiation or terminated during the hand-off process. When the blocking ratio exceeds some grade of service level, the capacity of the congested cell must be replanned using the call attempt data. However, most of the time, the measurements are inflated by the redials and the retrials. During the replanning process, the first step should be to calculate the effective load from the measured cumulative call statistics. In this paper, we provide simple-to-implement analytical models that compute the average number of retrials and redials per original call attempt using only the operations and maintenance center measurements. The effective load is then determined through appropriate scaling. That way, unnecessary waste of channels to sustain retrials and redials is avoided during the cellular capacity re-planning phase.

Human behavior modeling enables many applications for smart cities, smart homes, mobile phones and other domains. We present a hierarchical hidden Markov model for human activity recognition that uses semi-supervised learning to automatically learn the model parameters using only labeled data of the top-layer of the hierarchy. This significantly reduces the annotation requirements for such a model and simplifies the design of such a model, since the inherent structure of the activity is automatically learned from data. The design consideration that remains is the number of states used for representing the actions that an activity consists of. Using multiple real world datasets we show that the same model works both for the recognition of activities of daily living in a smart home and for recognizing office activities from audio data. We show how a variable number of action states per activity can result in a significant increase in performance over using a fixed number per activity. Finally, we show how the use of Bayesian and Akaike information criterion results in models using a sub-optimal set of action states, since a model using intuitively chosen set states is able to outperform them.

Energy-efficient green solutions are not only beneficial for the environment but also help to reduce the energy expenditure of the investors. Since base stations (BSs) of wireless cellular access networks are deployed to accommodate the peak-time traffic, they are underutilized most of the time. In this work, we try to save energy by both turning BSs on/off and adaptively adjusting their transmission power according to the current traffic conditions. To achieve that goal, we formulate a novel nonlinear programming model for the green dynamic BS planning (GDBP) problem to find the best possible topology which minimizes the energy consumption of the network while satisfying a certain grade of service (GoS). We derive a greedy heuristic called FastWISE to solve the formulated problem and compare our results with the results of a noncommercial optimization tool and numerous Monte Carlo experiments. It is shown that our GDBP scheme adaptively adjusts the network topology to the current traffic load and saves significant amount of energy without violating the GoS constraints, such as the probability of blocking and the coverage ratio.

Mobile sinks are proposed as a possible solution to the hotspot problem, which leads to the early death of the nodes close to the sink, due to the concentration of data traffic towards the sinks. However, the route updates employed by the source nodes to determine the position of the sinks introduce an overhead in terms of data reporting delays and energy consumptions. On the other hand, decreased frequency of route updates causes stale sink position information to be utilized for data packets which results in suboptimal data dissemination paths. In this paper, we investigate this inherent trade-off and provide an insight on how to fine tune the route update parameters of a mobile sink routing protocol. For this purpose, we define a system employing a simple routing protocol and determine the optimal operating points from the results obtained via simulations, under varying degrees of route updates and sink mobility.

Smartphones equipped with sensors can be used for monitoring simple daily activities (e.g., walking, climbing stairs etc.). The data collected via sensors need to be partially or completely annotated in order to be used in the training phase of learning algorithms. In order to ease the time consuming and burdensome annotation process, a mobile data collection and annotation application named Sensor Log is developed. The annotation feature and its ease of use make the developed application superior to existing systems. The application can be downloaded from the Android applications distribution platform.

The concentration of data traffic towards the sink in a wireless sensor network causes the nearby nodes to deplete their batteries quicker than other nodes, which leaves the sink stranded and disrupts the sensor data reporting. To mitigate this problem the usage of mobile sinks is proposed. Mobile sinks implicitly provide load-balancing and help achieving uniform energy-consumption across the network. However, the mechanisms to support the sink mobility (e.g., advertising the location of the mobile sink to the network) introduce an overhead in terms of energy consumption and packet delays. With these properties mobile sink routing constitutes an interesting research field with unique requirements. In this paper, we present a survey of the existing distributed mobile sink routing protocols. In order to provide an insight to the rationale and the concerns of a mobile sink routing protocol, design requirements and challenges associated with the problem of mobile sink routing are determined and explained. A definitive and detailed categorization is made and the protocols' advantages and drawbacks are determined with respect to their target applications.

In this paper, we propose a novel resource management technique, namely virtual cell layout (VCL), for rapidly deployable wireless networks that can be operated in hostile environments. In VCL, the area of communications is tessellated with regularly shaped fixed size virtual cells. The radio resources such as frequency carriers and scrambling codes are assigned to the fixed cells of this layout. The real cells, which do not have to be identical in size to the virtual cells, are mobile over VCL. Mobile base stations that make up the real cells use the radio resources assigned to the virtual cell in which they are located. The terminals of the system access to the network, as they are the terminals of an ordinary cellular network. When the terminals are not in the coverage of any mobile base station, VCL helps them to be organized into clusters. The performance evaluation of the proposed system shows that the VCL based architecture satisfies the rapid deployment requirement and gives an acceptable grade of service.

Wireless communications systems enable the end users to be mobile. The majority of the wireless communications networks are cellular networks. Several methods are developed to increase the performance of the cellular networks, which depends on the correct determination of the design parameters as well as the architecture of the system and the traffic requirements. In this study, we introduce a Simulated Annealing (SA) based method to determine the design parameters of a multi-tier cellular network, for which the implementation cost is minimized. The cellular system employs guard channels and allows calls to overflow to upper tiers. We conducted experiments with the SA-based technique on different example problems in two-tier cellular networks and obtained promising results.

The coexistence of a wide range of services with different quality of service (QoS) requirements in today's networks makes the efficient use of resources a major issue. It is desirable to improve network efficiency by adaptively assigning resources to services that have different bandwidth demands. Implementing Broadband Integrated Services Digital Networks (B-ISDN) therefore requires a network control scheme that can handle bursty traffic with unexpected fluctuations. The Asynchronous Transfer Mode (ATM) technology provides this flexibility by virtualizing network resources through the use of the virtual path (VP) concept. In this study, a method for designing a VP-based ATM network is proposed. The developed heuristic design algorithm applies VP routing and separation techniques to minimize the maximum link utilization under processing delay constraints. Each link is assigned a weight that reflects its current utilization. Using these weights, the VPs on highly utilized links are rerouted to less congested physical paths. The algorithm makes use of the equivalent bandwidth concept, which provides an efficient method to estimate capacity requirements of connection requests such that QoS requirements are met. The quality of the solutions achieved by the proposed method is compared to several competitors under varying network topologies and traffic conditions. The observations on the algorithm performance show that the developed method is able to facilitate an efficient use of network resources through the introduction of VPs.

Multihop lightwave networks are a means of utilizing the large bandwidth of optical fibers. In these networks, each node has a fixed number of transmitters and receivers connected to a common optical medium. A multihop topology is implemented logically by assigning different wavelengths to pairs of transmitters and receivers. By using tunable lasers or receivers, it is possible to modify the topology dynamically when node failures occur or traffic loads change. The reconfigurability of logical multihop lightwave networks requires that optimal topologies and flow assignments be found. In this article, optimization of these logical topologies by genetic algorithms is investigated. The genetic algorithm takes topologies as individuals of its population, and tries to find optimal ones by mating, mutating and eliminating them. During the evolution of solutions, minimum hop routing with flow deviation is used to assign flows, and evaluate the fitness of topologies. The algorithm is tested with different sets of parameters and types of traffic matrices and the solutions are compared against histograms of random samples from the solution space. These tests show that the solutions found by the genetic algorithm are comparable with and in some cases better than those found by existing heuristic algorithms.

The main functionality of a surveillance wireless sensor network is to detect unauthorized traversals in a field. In this paper, we develop a formulation to determine the probability of detecting a randomly positioned target by a set of binary sensors to serve as the deployment quality measure. This formulation leads to a recipe to determine the number of sensors required to deliver a certain deployment quality level. The sensing- and communication-neighbor degrees which can be used as design criteria in a sensor network are defined and calculated. The model. is verified by simulations whose outcomes closely match the analytical results.