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Flexibility and energy efficiency are considered two principal requirements of future fifth generation (5G) systems. From an architectural point of view, centralized processing and a dense deployment of small cells will play a vital role in enabling the efficient and dynamic operation of 5G networks. In this context, reconfigurable hotspots will provide on-demand services and adapt their operation in accordance to traffic re quirements, constituting a vital element of the heterogeneous 5G network infrastructure. In this paper we present a reconfigurable hotspot which is able to flexibly distribute its underlying communication functions across the network, as well as to adapt various parameters affecting the generation of the transmitted signal. The reconfiguration of the hotspot focuses on minimizing its energy footprint, while accounting for the current operative requirements. A real-time hotspot prototype has been developed to facilitate the realistic evaluation of the energy saving gains of the proposed scheme. The development flexibly combines software (SW) and hardware (HW) accelerated (HWA) functions in order to enable the agile reconfiguration of the hotspot. Actual power consumption measurements are presented for various relevant 5G networking scenarios and hotspot configurations. This thorough characterization of the energy footprint of the different subsystems of the prototype allows to map reconfiguration strategies to different use cases. Finally, the energy-aware design and implementation of the hotspot prototype is widely detailed in an effort to underline its importance to the provision of the flexibility and energy efficiency to future 5G systems. ; This work was supported by the European Commission in the framework of the H2020-ICT-2014-2 project Flex5Gware (Grant agreement no. 671563). The work of CTTC was also partially supported by the Generalitat de Catalunya (2017 SGR 891) and by the Spanish Government under project TEC2014-58341-C4-4-R.

In this article we discuss 'slanty design', which incorporate three new principles into a conventional user-centered design process. These are designing for non-goals (things you wish the user not to be able to do); creating anti-usability (designing so that it is difficult to achieve the non-goals); and clean design (solutions without unwanted side-effects that then have to have solutions designed for them). Slanty design incorporates many of the concepts of socio-technical approaches, and is explained using a variety of examples, including an airport baggage carousel, and the remaining challenges outstanding are described.

PurposeTrust is an increasingly important requirement for any business and as a result has become a contemporary design criterion for business processes. However, the literature to date is very much focused on the technical (security) aspects, which are provider centric, as opposed to trust that is customer centric. In this paper, the authors extended an initial meta-model of trust-aware process design by proposing a way to capture trust-intensity for four trust dimensions, i.e. input, people, process and output and an organizational trust position. The authors also investigate the deployment of the extended meta-model in practice.Design/methodology/approachAn extensive literature study is conducted to derive an understanding of the dimension's customer trust when interacting with an organization. Based on the findings of the literature review and a previously developed trust meta-model, the authors propose a way to describe an organizational trust position, i.e. the depiction of how much uncertainty is prevalent in the trust dimensions. Next, the authors conducted an exploratory case study using secondary data to validate the extended meta-model.FindingsThe case study demonstrated the applicability of the extended trust meta-model and derived actionable practices. In this case, the Indonesian food delivery company GoFood, the authors identified trust concerns in the input, process, resources and output of their business at the start of their operations. Since then, GoFood took specific actions to reduce their operational, behavioral and perceived uncertainty and these identified trust concerns. To a lesser degree, GoFood has managed vulnerability issues and invested in measures to increase customers' confidence. As a result of reduced uncertainties, GoFood's business has grown and became the number one in food service delivery in Indonesia.Research limitations/implicationsThe approach to capture trust (in the trust dimensions) is still a simplified version and a pre-step for a fully developed management tool or method. The use of a secondary data from a single case study also limits the validity and generalizability of the findings.Practical implicationsThe extended meta-model proposed in this paper has several implications related to the organization's BPM capabilities. The result also demonstrates how trust measures related to reducing uncertainty, reducing vulnerability and increasing confidence can be applied in practice. Strategies used by the case company presented here such as rating systems to increase confidence can be used by other firms within a similar context.Social implicationsHaving an empirically validated framework for the management of trust, allows organizations to execute an operational model for the development of trusted engagement with the main benefactor being the customer.Originality/valuePrevious trust-related studies focused on conceptual ideas only, relied on fictive examples or were very much focused on the technical (security) aspects of business processes. This study is the first empirical validation of a trust meta-model that serves managers to understand their trust position and to guide trust-building actions.

A tactical sensor network is a representative safety-critical environment that should satisfy strict guarantee of the requirements of tactical traffic. However, because of the lack of infrastructure in a military network environment, resource constraints on wireless channel and nodes can cause problems such as network congestion and packet collision. If critical tactical data is lost or does not arrive on time, it can degrade the efficiency of military operations and even threaten the survival of soldiers. To resolve this critical issue, we propose a situational backoff reset algorithm that utilizes a quality of service (QoS) field information to determine the priority of received tactical packets and control the deferral time of low-priority traffic. From a packet routing path connectivity perspective, we propose a branch node-based routing algorithm in order to provide a resilient path by excluding the isolated single path. Our simulation results demonstrate that the proposed solution can prioritize tactical traffic from the channel preemption perspective and construct a robust end-to-end path avoiding an isolated single path.

Wearable sensing systems are becoming widely used for a variety of applications including sports, entertainment, and the military. These systems have recently enabled a variety of medical monitoring and diagnostic applications. Such sensing systems have high potential to significantly improve the quality of life for large segments of the population and enable conceptually new types of applications. However, various research challenges including energy sensitivity and semantic complexity must be addressed before these devices can reach their full potential in improving our lives. The need for multiple sensors, high frequency sampling and constant monitoring leads these systems to be power-hungry and expensive with a short operation lifetime. In addition these systems generate a massive amount of data, where designing efficient and effective data mining algorithms to interpret and analyze the data is very costly due to field experts' involvement. This dissertation presents a methodology that takes advantage of contextual and semantic properties in human physiological behavior to enable efficient design and optimization of such systems from the data and information point of view. The methodology uses combinatorial modeling and simultaneous minimization to reduce the wireless communication and local processing power consumption. The effectiveness of this technique is shown on an insole instrumented with 99 pressure sensors placed in each shoe, which is used for human gait analysis. Further, the proposed methodology is used to design unsupervised data mining techniques to extract information such as frequent or rare events and patterns from collected multi-dimensional time series data of wearable sensing devices, where high level of noise and uncertainty is inherent. This approach transforms multi-dimensional time series data to combinatorial space and constructs behavior models, which is used for frequent and rare event detection and pattern classification. The effectiveness of this method is demonstrated by applying this technique to discovery and classification of frequent human activities and abnormalities.

The current and envisaged increase of cellular traffic poses new challenges to mobile network operators (MNO), who must densify their radio access networks (RAN) while maintaining low capital expenditure and operational expenditure to ensure long-term sustainability. In this context, this paper analyzes optimal clustering solutions based on device-to-device communications to mitigate partially or completely the need for MNOs to carry out extremely dense RAN deployments. Specifically, a low-complexity algorithm that enables the creation of spectral efficient clusters among users from different cells, denoted as enhanced clustering optimization for resources' efficiency is presented. Due to the imbalance between uplink and downlink traffic, a complementary algorithm, known as clustering algorithm for load balancing, is also proposed to create nonspectral efficient clusters when they result in a capacity increase. Finally, in order to alleviate the energy overconsumption suffered by cluster heads, the clustering energy efficient algorithm (CEEa) is also designed to manage the tradeoff between the capacity enhancement and the early battery drain of some users. Results show that the proposed algorithms increase the network capacity and outperform existing solutions, while, at the same time, CEEa is able to handle the cluster heads energy overconsumption. ; Grant numbers : This work has been funded by the CellFive (TEC2014-60130- P) projects as well as the AGAUR project the Catalan Government (2014 SGR 1551).© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

An embedded system is a small autonomous computer system that is encapsulated in the device it is controlling. Examples of device with embedded systems are TVs, microwaves, and dishwashers. A modern car can hold as much as 60 microprocessors. Embedded systems sales are rapidly increasing. In fact processor sales for embedded system are much larger than those for personal computers. PC processors only represents 2 percent of all processor sales. The division of EISLAB at Luleå University of Technology focuses on research on Embedded internet systems (EIS). Embedded Internet Systems are embedded systems used to collect, process and distribute data over the Internet. EIS devices is a rapidly growing field. The reduced physical size and price of EIS sensors make them attractive to use in a wide range of applications such as; environmental monitoring, industrial, health care, and military surveillance. The vision of EISLAB is sensors with lifetimes in the range of years that will fit within a few cubic centimeters. The sensors developed at EISLAB are based on commercial-of-the-shelf-components (COTS). Using COTS-components reduces development time and cost for prototypes and small series products. All communication is handled using standardized protocols to give the device access to available communication infrastructure, such as cellular networks and the Internet. As most of the nodes are battery operated the dominant constraint for EIS devices is power consumption. This thesis presents our work to address this topic at a high level of abstraction. The first paper includes the development of a power aware design methodology for EIS devices. In the second paper the proposed design methodology is applied to a bluetooth-equipped device. The third paper discusses the problem of reducing power consumption of an always connected EIS device, showing the tradeoffs between power consumption and response time. ; Godkänd; 2005; 20060922 (ysko)

In this paper, we study wireless networked control systems with energy harvesting sensors. Multiple sensors share a wireless medium over which they transmit measurements to their respective controllers, and due to the shared medium, packet collisions occur if sensors transmit simultaneously. To alleviate this problem, we propose random access policies that satisfy a desired control performance on each control loop, while also satisfying the energy constraints imposed by the energy harvesting process. The optimal scheduling policy is shown to follow a simple thresholding operation. Moreover, we provide a stochastic dual method for their computation, which is shown to be decoupled across sensors. Finally, we verify numerically the properties of the proposed policy. ; Grant numbers : This work was partially supported by the Catalan government under grant SGR2014-1567; the Spanish government under grant TEC2013-44591-P (INTENSYV), and grant PCIN-2013-027 (E-CROPS).

Harvesting energy in the human environment has been identified as an effective way to charge the body sensor nodes in wireless body area networks (WBANs). In such networks, the capability of the nodes to detect events is of vital importance and complements the stringent quality of service (QoS) demands in terms of delay, throughput, and packet loss. However, the scarce energy collected by human motions, along with the strict requirements of vital health signals in terms of QoS, raises important challenges for WBANs and stresses the need for new integrated QoS-aware energy management schemes. In this paper, we propose a joint power-QoS (PEH-QoS) control scheme, composed of three modules that interact in order to make optimal use of energy and achieve the best possible QoS. The proposed scheme ensures that a sensor node is able to detect the medical events and transmit the respective data packets efficiently. Extensive simulations, conducted for different human activities (i.e., relaxing, walking, running, and cycling), have shown that the application of PEH-QoS in a medical node increases the detection efficiency, the throughput, and the energy efficiency of the system. ; Grant numbers : This work has been partially funded by the Research Projects AGAUR the Catalan Government 2014-SGR-1551.© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.