Angelos Antonopoulos

Green distance-aware base station sleeping algorithm in LTE-Advanced

In this paper, we propose a switch on/off algorithm for Base Stations (BSs), which exploits the knowledge of the distance between the User Equipments (UEs) and their associated BS. Our novel approach hopes to provide an improvement to the problem of energy consumption. The major concern lies on reducing the energy consumption of the telecommunication networks by optimizing the power utilization without sacrificing the offered Quality of Service (QoS). Our proposed scheme achieves a significant power saving, based on switching off the Base Stations that are underutilized during low traffic periods (especially during night) in the LTE-Advanced.

Energy efficient network coding-based MAC for cooperative ARQ wireless networks

In this paper we introduce a network coding-aided energy efficient Medium Access Control (MAC) protocol that coordinates the transmissions among a set of relay nodes which act as helpers in cooperative Automatic Repeat reQuest-based (ARQ-based) wireless networks. Applying network coding techniques, we achieve to increase the energy efficiency of the network without compromising the system performance in terms of Quality of Service. Our proposed solution is evaluated by both analytical and simulation results.

A survey on M2M systems for mHealth: a wireless communications perspective.

In the new era of connectivity, marked by the explosive number of wireless electronic devices and the need for smart and pervasive applications, Machine-to-Machine (M2M) communications are an emerging technology that enables the seamless device interconnection without the need of human interaction. The use of M2M technology can bring to life a wide range of mHealth applications, with considerable benefits for both patients and healthcare providers. Many technological challenges have to be met, however, to ensure the widespread adoption of mHealth solutions in the future. In this context, we aim to provide a comprehensive survey on M2M systems for mHealth applications from a wireless communication perspective. An end-to-end holistic approach is adopted, focusing on different communication aspects of the M2M architecture. Hence, we first provide a systematic review of Wireless Body Area Networks (WBANs), which constitute the enabling technology at the patients side, and then discuss end-to-end solutions that involve the design and implementation of practical mHealth applications. We close the survey by identifying challenges and open research issues, thus paving the way for future research opportunities.

Game theoretic D2D content dissemination in 4G cellular networks

The widespread proliferation of mobile devices has motivated Device-to-Device (D2D) communications as a means of cell offloading toward better Quality of Service (QoS) and higher energy efficiency. Although Wi-Fi networks have the lions share regarding the D2D communications in the unlicensed spectrum, it is uncertain whether they constitute the best option as technology evolves. In particular, the increasing transmission data rates, the novel interference cancelation techniques, as well as the potential of centralized network support, stress the need for new Medium Access Control (MAC) protocols, especially in content dissemination scenarios where all nodes share the same goal. In this article we study the suitability of Wi-Fi technology in content dissemination scenarios with multiple available source nodes, and we propose two energy-aware game theoretic MAC strategies (a distributed and a network-assisted) as possible alternatives. Our simulation results show the effectiveness and the flexibility of our proposed solutions, highlighting the necessity for new MAC designs.

QoS-Aware Energy Management in Body Sensor Nodes Powered by Human Energy Harvesting

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.

Information Exchange in Randomly Deployed Dense WSNs With Wireless Energy Harvesting Capabilities

As large-scale dense and often randomly deployed wireless sensor networks (WSNs) become widespread, local information exchange between colocated sets of nodes may play a significant role in handling the excessive traffic volume. Moreover, to account for the limited life-span of the wireless devices, harvesting the energy of the network transmissions provides significant benefits to the lifetime of such networks. In this paper, we study the performance of communication in dense networks with wireless energy harvesting (WEH)-enabled sensor nodes. In particular, we examine two different communication scenarios (direct and cooperative) for data exchange and we provide theoretical expressions for the probability of successful communication. Then, considering the importance of lifetime in WSNs, we employ state-of-the-art WEH techniques and realistic energy converters, quantifying the potential energy gains that can be achieved in the network. Our analytical derivations, which are validated by extensive Monte-Carlo simulations, highlight the importance of WEH in dense networks and identify the tradeoffs between the direct and cooperative communication scenarios.

Game theoretic approach for switching off base stations in multi-operator environments

The emerging increase of the number of Base Stations causes redundant energy consumption, especially during low traffic periods, when the Base Stations capacity is underutilized. In this paper, we study energy efficiency issues in multi-operator mobile networks. Our primary goal is to save energy, without compromising the offered Quality of Service, by switching off the excessive Base Stations. To this end, we propose a novel game theoretic strategy using cost-based functions to decide the best suitable Base Stations to remain active. Mathematical analysis and simulations demonstrate that the proposed scheme can significantly reduce the energy consumption.

Energy-efficient infrastructure sharing in multi-operator mobile networks

Network infrastructure sharing and base station switching off mechanisms have been recently introduced as promising solutions toward energy and cost reduction in cellular networks. Although these techniques are usually studied independently, their combination offers new alternatives to MNOs for serving their users and could potentially provide them with additional benefits. In this article we introduce the concept of intra-cell roaming-based infrastructure sharing, where the MNOs may switch off their BSs and roam their traffic to active BSs operated by other MNOs in the same cell. Motivated by the coexistence of multiple operators in the same area, we present possible network deployments and architectures in current and future cellular scenarios, discussing their particular characteristics. In addition, we propose an innovative distributed game theoretic BS switching off scheme, employing an integrated cost function that takes into account all the different cases for a given operator to serve its own traffic (i.e. through active BSs of neighboring cells or exploiting intra-cell roaming-based infrastructure sharing). Finally, we demonstrate some indicative simulation results in realistic scenarios to quantify the potential energy and financial benefits that our proposed scheme offers to the MNOs in multi-operator environments, providing them with the necessary incentives to participate in the infrastructure sharing.

Reliable MAC design for ambient assisted living: moving the coordination to the cloud

AAL technologies constitute a new paradigm that promises quality of life enhancements in chronic care patients and elderly people. From a communication perspective, they involve heterogeneous deployments of body and ambient sensors in complex multihop topologies. Such networks can significantly benefit from the application of cooperative schemes based on network coding, where random linear combinations of the original data packets are transmitted in order to exploit diversity. Nevertheless, network coordination is sometimes required to obtain the full potential of these schemes, especially in the presence of channel errors, requiring the design of efficient, reliable, and versatile MAC protocols. Motivated by the recent advances in cloud computing, we investigate the possibility of transferring the network coordination to the cloud while maintaining the data exchange and storage at a local data plane. Hence, we design a general framework for the development of cloudassisted protocols for AAL applications and propose a high-performance and error-resilient MAC scheme with cloud capabilities.

Smart HVAC Control in IoT: Energy Consumption Minimization with User Comfort Constraints

Smart grid is one of the main applications of the Internet of Things (IoT) paradigm. Within this context, this paper addresses the efficient energy consumption management of heating, ventilation, and air conditioning (HVAC) systems in smart grids with variable energy price. To that end, first, we propose an energy scheduling method that minimizes the energy consumption cost for a particular time interval, taking into account the energy price and a set of comfort constraints, that is, a range of temperatures according to users preferences for a given room. Then, we propose an energy scheduler where the user may select to relax the temperature constraints to save more energy. Moreover, thanks to the IoT paradigm, the user may interact remotely with the HVAC control system. In particular, the user may decide remotely the temperature of comfort, while the temperature and energy consumption information is sent through Internet and displayed at the end users device. The proposed algorithms have been implemented in a real testbed, highlighting the potential gains that can be achieved in terms of both energy and cost.