A Roadmap for a Green Interface Selection Standardization over Wireless HetNets Mehmet Fatih Tuysuz Department of Computer Engineering, Harran University, Sanliurfa, Turkey
[email protected]
Ramona Trestian School of Science and Technology, Middlesex University, London, UK
[email protected]
Abstract—Wireless heterogeneous networks (HetNets) have been widely deployed in parallel with the dramatic increase of smart mobile devices. Nowadays, people use these devices to access the Internet, communicate, socialize and handle their short or longterm businesses. As these devices rely on their batteries, energyefficiency has become one of the major issues in both academia and industry. Due to terminal mobility, variety of Radio Access Technologies (RATs) and need to be always best connected (ABC) to the Internet anytime and anywhere, energy-efficient interface selection has to be taken into account carefully. In this context, this roadmap1 intends to raise the awareness of energy efficiency, and to highlight a green interface selection process in which additional standardization is needed. The roadmap first describes essential rules of energy-efficient interface/network selection procedure. Then, it discusses future policies of green interface selection standardization for smart mobile devices, from the perspective of governments, non-governmental organizations (NGOs) and companies.
effort, etc.); different device types (e.g., smartphones, tablets, laptops, etc.); different network technologies (e.g., WLANs, LTE, WiMAX) and different user preferences.
Keywords—Energy efficiency, green standardization, interface selection, wireless HetNets.
In order to fulfil the increasing requests of mobile users, next generation wireless systems will be utilizing cooperative heterogeneous wireless technologies that enable users to be always best connected at anytime and anywhere [2]. The main promise of the heterogeneous network integration is to provide mobile users with high performance and wide coverage. In terms of energy conservation, the current trends, such as increasing electricity costs, reserve limitations, and increasing emissions of carbon dioxide (CO2) are shifting the focus of Information and Communication Technologies (ICT) towards energy-efficient well-performed solutions. Even though governments and companies are now aware of the importance of energy conservation requirements and carbon emissions reductions, it is obvious there will still be a continuous increase in the coming years [3]. As stated by the SMART 2020 study [4], ICT-based CO2 emissions are rising at a rate of 6% per year. With such a growth ratio, it is expected that CO2 emissions caused by ICTs will reach 12% of worldwide emissions by 2020. The work in [5] estimates the CO2 emissions over six ICT categories and show that mobile telecoms correspond to a 9% CO2 emissions among all categories. Besides, the dense deployment of Point of Attachments (PoAs), which is required to satisfy the ever-growing demand of performance and coverage, has been causing the increase of wireless networks’ energy consumption with an impact on global CO2 emissions. Recently, these increases have received remarkable attention from both industry and academia [6]-[8]. In order to decrease the overall energy consumption, the Greentouch consortium [9] and major European Projects like EARTH [10] and Mobile VCE [11] focus on infrastructurebased energy savings for wireless networks at the system
I. INTRODUCTION Nowadays, wireless connectivity has become a daily routine in everyone’s daily life. Users are expected to be able to connect wirelessly to the Internet anytime and anywhere, while maintaining high performance and Quality of Service (QoS) support. The increase in the usage number of smart mobile devices together with the mass-market adoption of video-based applications, such as IPTV, video streaming, HDTV, 3DTV, etc. will place substantial pressure on both the underlying network technology and the content processing. Cisco predicts that by 2019 the smart mobile devices will be generating 97% of the total mobile data traffic, out of which 72% will be video [1]. To cope with this explosion of data traffic, the next generation networks may integrate various radio access technologies (RAT), such as: Wireless Local Area Networks (WLAN), Worldwide Interoperability for Microwave Access (WiMax), Long Term Evolution (LTE), etc. However, there is no single wireless RAT that can simultaneously offer low-latency, high-bandwidth and wide coverage with high QoS levels to the mobile users. In this context, the network operators will be faced with real challenges in ensuring the Always Best Experience to the mobile users that are seamlessly roaming within this HetNet Environment as seen in Fig. 1. The mobile user will be facing a complex decision when selecting the best network to connect to, especially due to the heterogeneity of the selection criteria, such as: the applications requirements (e.g., video, voice, best 1 This work was supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) under Grant No: 114E075.
Fig. 1. Example Scenario - Next Generation HetNet Environment
978-1-4673-9526-7/15/$31.00 ©2015 IEEE
A. Standards which Support Network Selection The IEEE 802.21 Media Independent Handover (MIH) standard [14] considers the interoperability aspects between heterogeneous networks enabling the optimization of handover between heterogeneous networks. The standard could facilitate the handover process by providing the mobile devices with link-layer information of different RATs and battery-level status. Hence, it improves not only the interface selection process and user experiences, but also energy efficiency, assisting both mobile and network-initiated handovers. MIH provides abstract services that enable the information exchange between higher and lower layers through a mediaindependent framework and the associated services [15]. IEEE 802.21 MIH standard defines three main services that assist the handover process: (1) Media Independent Event Services (MIES) defines events, such as Link_Up, Link_Down, which represent the changes in the link quality; (2) Media Independent Command Service (MICS) provides commands to control the link state; (3) and the Media Independent Information Service (MIIS) that provides mobile devices with fast and energy-efficient channel scanning results. The MIIS supports the distribution of the network information and may provide as many information as possible to the PoAs, such as the available PoA list and their coordinates (connectivity graph), the available services, channel utilization ratios of each PoA, etc.
PoA3
Station
PoA2
d1(2)
d1(5) PoA1
PoA5
6)
PoA7
d 1(
r
d1(
3) d1(
In wireless heterogeneous networks, interface selection or vertical handover is the procedure of shifting an ongoing call or a data session from one PoA to another. Consequently, this procedure allows mobile stations to dynamically associate with the most suitable PoAs among available ones. If a handover occurs within the domain of a RAT, the process is known as horizontal handover. In contrast, vertical handover (VHO) takes place among different RATs. As stations in wireless heterogeneous networks continuously seek channels to initiate horizontal or vertical handovers, designing an energy-efficient interface/network selection scheme is important to minimize the energy consumption while still maintaining the QoS. Handover duration and its accuracy is also essential for the energy efficiency. It is because, a possible improper association to a new network may let stations consume even more power than before until a proper association, if ever, is selected.
PoA4
4)
INTERFACE SELECTION AND HANDOVER STRATEGIES
d1(7
II.
Traditionally, handover is performed based on the Received Signal Strength Indicator (RSSI), such that stations select a PoA that has the strongest RSSI. Existing handover approaches accomplish energy savings either by minimizing the total channel scanning duration or by associating with the most energy-efficient PoA according to the signal strength levels. However, as each RAT have particular characteristics, in order to increase the energy efficiency and handover accuracy, an energy-efficient vertical handover approach or interface selection, must evaluate each RAT separately by making use of local and network related parameters.
)
level. The major aim of these projects is to design and implement pioneering approaches for green operation of wireless networks. However, to date, the projects have only examined the optimization of homogeneous wireless systems. Since, current mobile devices are equipped with multiple network interface cards to operate within the HetNet environment in a flexible way, energy-centric optimization is also an important issue and has to be investigated carefully to enable energy conservation and reduced carbon emissions. Interworking of heterogeneous networks may increase network performance and provide seamless mobility for mobile users. However, this flexibility may cause additional energy consumption on the mobile device which in turn will decrease the communication time. Mobile devices deeply depend on the energy provided by their batteries, and hence their running time is limited. Moreover, processing power doubles almost every two years according to the Moore’s law. However, the progress in batteries did not even double over the last decade [12]. In this regard, the design concept of protocols, networks and hence mobile devices have started to change in both academia and industry by keeping the energy efficiency in mind. Therefore, currently, the bottleneck of the mobile system design is not only the transmission rate, but even more the energy limitation since consumers ask for new energy-hungry services [13]. To this extent, this paper presents a roadmap towards green interface selection standardization within a HetNet environment. The existing standards and industry solutions for network selection strategies within a HetNet environment are summarized. A small study is presented on the impact of handover on the energy consumption of a mobile device when performing Video on Demand (VoD) over an LTE HetNet small cell environment. Essential rules of energy-efficient interface selection procedure are formulated for a better understanding of what is technically needed for optimization of energy efficiency. Moreover, an equation for predicting the expected power consumption of each interface is derived. Finally, future policies of green interface selection for mobile devices are discussed from the perspective of governments, non-governmental organizations (NGOs) and companies.
PoA6
Fig. 2. Example of a distance-based connectivity graph provided by MIIS
Fig. 2 shows an example of a distance-based connectivity graph provided by the IEEE 802.21 MIIS, where r is the transmission range of each PoA, di(n) is the lineal distance between the PoAi and PoAn. Using this information, mobile devices will be able to scan (unicast scanning) only the PoAs the MIIS provides and hence, they will be able to reduce the total scanning time, eliminating the channels that are not in the
connectivity graph. Consequently, using the IEEE 802.21 protocol, mobile devices will be able to scan less than n (total number of channels) channels and hence, reduce both the total scanning time and the energy consumed in scanning phase. The Access Network Discovery and Selection Function (ANDSF) was defined by the 3GPP standard 23.402 [16] to enable the interworking of 3GPP (e.g., UMTS, LTE) and non3GPP networks (e.g., CDMA, WiFi, WiMAX). The ANDSF mainly provides three types of information: (1) Inter system mobility policy (provides interface selection rules for mobile devices with only one active access network connection), (2) Inter system routing policy (provides interface selection rules for mobile devices with potentially more than one active access network connection) and (3) Discovery information (provides list of available access networks including access type technology, radio access networks identifier, etc.) [17]. Moreover, the 3GPP release 12 standardization provides an enhanced version of Radio Access Technology Frequency Selection Priority (RFSP) enabling the support for the 3GPP and WiFi Radio Interworking. This will enable the QoS provision and improved mobile device battery consumption by providing a tight cooperation between the WiFi technology and the 3GPP networks. Consequently, ANDSF protocol enables mobile devices that are associated with an LTE interface to discover other RATs, such as WiFi or WiMAX in the vicinity without switching their interfaces on. Hence, this procedure also reduces both the total scanning time and the energy consumed in the scanning phase as the IEEE 802.21 protocol. IEEE 802.11u [18] is an amendment to the base IEEE 802.11-2007 standard that enables the interworking of 802.11 networks with external networks. The standard defines an Access Network Query Protocol (ANQP) that provides the mobile device with information related to the neighboring networks that is not advertised in beacons. This enables the pre-association services and facilitates the network selection process even prior to network association. B. Industry Solutions for Network Selection In the current environment, as network operators are facing significant increase in data traffic and as the mobile networks evolve towards all-IP networks, the Wi-Fi and cellular interworking technologies remain essential. A popular solution for network operators to cope with the traffic demands and to expand the capacity of their network is the mobile data offloading technique which enables transferring some of the traffic from the core cellular network to Wi-Fi or femtocells at peak times and key locations (e.g., home, office, public HotSpot, etc). Hotspot 2.0 [19] is the industry initiative build on top of the IEEE 802.11u standard that makes use of ANQP for public-access Wi-Fi networks. Hotspot 2.0 improves the user experience by enabling automatic seamless connectivity to Wi-Fi hotspots. iPass Mobile Network2 is one of the largest commercial Wi-Fi provider which offers more than 20 million Wi-Fi hotspots around the world so that users are well connected anywhere they roam.
The HetNets Wi-Fi offload solution has been adopted by many service providers. For example, in United Kingdom, ‘O2’ offers the ‘Tu Go3’ application to their customers enabling them to use their mobile numbers to call or text over the Wi-Fi network. Same approach is adopted by ‘Three’, with the ‘Three inTouch4’ application. In this way, their customers can avail of a wider coverage and service offering. Another strategy of network selection intelligence for offloading the traffic between the mobile and Wi-Fi networks automatically and enabling the operators to ensure consistency across their access networks and offer improved Quality of Experience (QoE) to their customers, is offered by Openet5. In this context, the HetNet small cells environment is seen as a promising solution especially as the Wi-Fi connections can offer increased data rates and are more battery-efficient. However, selecting the right network to connect to can be difficult for the regular mobile user and efficient network selection mechanisms that will automatically select the best value network for the user, are needed. III.
With the deployment of small cells for next generation networks, such as LTE-Advanced, the operators can avail from improved capacity at low cost. Even though this solution presents advantages for the network operators, a HetNet small cell environment results in an increased number of handovers at the mobile device side which can result in further increase in energy consumption [20]. Furthermore, due to the growth of the video content usage, ensuring a seamless experience at high quality levels to the end-user has become a challenge, making the battery lifetime of the mobile device the main impediment of progress. This section looks at the impact of the handover process on the energy consumption of an Android mobile device, in the context of Video on Demand (VoD) over a LTE HetNet small cell environment. A. Experimental Test-Bed
Fig. 3. LTE Small Cell Experimental Test-Bed Setup
An LTE-enabled HTC One SV mobile device was used to measure the energy consumption when performing VoD during the handover over the LTE small cell environment illustrated in Fig. 3. The test-bed consists of: (1) the Power 3 4
2
iPass Mobile Network – www.ipass.com
HANDOVER IMPACT ON ENERGY CONSUMPTION
5
Tu Go - http://www.o2.co.uk/apps/tu-go Three inTouch - http://www.three.co.uk/Discover/Three_inTouch Openet - www.openet.com
Consumption Monitor which uses an Arduino Duemilanove board connected to the mobile device and a laptop that stores the measurements; (2) a multimedia server that streams a 10 minute long high quality Big Buck Bunny6 video clip encoded at 1920Kbps, with a resolution of 800x448 pixels and a frame rate of 30fps; (3) The Amari LTE 1007 emulates the LTE small cell environment and provides a fully software-based LTE base station solution running on a PC with the USRP N210 and a SBX daughterboard as the radio frontend. B. Results Energy measurements were collected for the high quality video stream to the Android mobile devices under an increasing number of handovers within the LTE small cell environment. The video play-out was scaled to the device screen resolution and the background activity was kept the same between the tests. Each test was repeated three times and the average values are used. The handover process was emulated by increasing the transmission power of one cell and decreasing it for the second cell. The mobile device automatically handovers to the cell with the highest received signal strength. The results are listed in Fig. 4, and it can be seen that, as expected, when the number of HOs is increasing the energy consumption will increase as well. For example, one handover will increase the energy consumption by 9% whereas a total of five handovers will account for up to 23% increase in energy consumption when compared with the case of no handover.
Fig. 3. Avg. Energy Consumption for VoD over LTE Small Cell
In this context, an efficient proactive handover strategy, where the mobile device could adapt the multimedia stream to a lower quality level ahead of the handover process could conserve the battery lifetime of the mobile device [20]. IV. RULES OF ENERGY-EFFICIENT INTERFACE SELECTION In order to perform an energy efficient interface selection, rather than using a full set of parameters, a convenient set of information must be gathered and transferred to the decision phase. In this context, mobile devices must seek for available networks (network discovery) at first to detect whether there is a PoA to associate with in the vicinity. Consequently, some actions/rules can be formulated to ensure energy savings before the handover execution (throughout the information gathering and decision phase), as listed below: 6 7
Big Buck Bunny - http://www.bigbuckbunny.org Amari LTE 100 – www.amarisoft.com
Rule 1: Initially, a mobile device should not use more than one radio interface simultaneously. When a mobile device has more than one radio interface active simultaneously, it consumes scarce resources, such as processing power and battery. Rule 2: Frequency of information gathering is crucial for an energy-efficient handover. Some approaches initiate information gathering or the discovery process only when the current network is no more able to handle the ongoing connection, or in other words, information gathering is initiated only when the measured RSSI is below a certain threshold. This way, as long as the channel allows mobile devices to be connected and to communicate, these devices only perform their regular actions, meaning there is no extra processing time and no additional energy consumption. At first sight, this procedure seems energy efficient. However, there might be another PoA(s) in the vicinity that will let the device consume less power in case of an association scenario. Since the device does not perform a discovery process, as the measured RSSI is not below a certain threshold, it consumes more power as long as it is associated with its old PoA. Therefore, this procedure may not always be energy efficient. In contrast to the first approach, some approaches continuously or periodically seek for available networks and collect related information to let mobile devices perform fast and accurate handover. This is also not an energy efficient approach as continuous or periodic scanning causes devices to consume additional energy and to interrupt their regular action, hence impacting their performance. In this regard, a dynamic algorithm that increases or decreases the frequency of information gathering can provide an optimal energy efficiency. In short, interface selection algorithms must increase the frequency in case the device is moving or the channel condition rapidly changes. In contrary, the algorithm must decrease the frequency in case the device is stable and channel condition is fixed or slowly changes. Rule 3: Instead of requesting network-related information one by one from the associated PoA (network-side assisting with many message exchanges), in case a vertical handover standard (MIH or ANDSF) is available, stations must request all the information these standards offer at once. Rule 4: It is also possible for mobile devices to obtain many network-related information without making use of the vertical handover standards. However, in order to collect this information, mobile devices have to transmit additional frames (requests). These additional frames may also take significant time (one round-trip-time for each information) and processing overhead for mobile devices. Consequently, the device may be too late to handover, waiting for networkrelated information or may consume an important portion of unnecessary power. Therefore, rather than a full set of information, gathering only the related and convenient information lets mobile devices achieve fast and energyefficient interface/network selection. Rule 5: Making use of mobile assisted handover, mobile devices can process their local information and transfer it to the decision stage. For mobile assisted handover, gathering this information usually takes a very short time and consumes such a small amount of power (unless the information is obtained by additional hardware support such as gps,
accelerometer, etc.) compared to the time and power consumption in case of network assisted handover. Hence, for an optimal energy efficient handover opportunity, all set of local information supported by the device can be processed locally before transferring them to the decision stage. Rule 6: An important portion of energy consumption can be reduced with the definition of user preferences as well. Making use of the user preferences, decision algorithms increase the weight of the energy priority and hence, association to an energy-efficient PoA would be performed for the device in a possible handover scenario. Rule 7: Even though the total energy consumed in the decision stage is not as much as in the information gathering stage, various network interface selection methods (costfunction, fuzzy-logic, context-aware, user-centric, cognitive, game theoretic, reputation-based, etc.) used in the decision stage may also cause different amount of power consumption. Rule 8: Mobile device resource (CPU, memory, Input/Output operations, electrical power, etc.) management by preventing resource leaks and dealing with resource contention increases both performance and energy efficiency of the whole system and hence, the interface selection process. Rule 9: Marking the networks that the device is connected during the day (according to specific time and location) enables proactive network/interface selection without (or with limited) network discovery process as the same networks/interfaces, are involved in the decision process. Thus, historical information can be used to reduce the power consumption during network discovery. Rule 10: It is also important to choose a network/interface according to the traffic type and transport protocol (TCP/UDP) used by the application. UDP and TCP frames have different amount of bandwidth requirements. When designing an energy efficient network selection strategy, the underlying transport protocol of the application should be considered. Rule 11: Last but not the least, while one of the wireless radio interfaces of a mobile device is active, reducing some amount of energy consumption is also possible by utilizing the transmission power control (TPC) [21], frame size adaptation, and data compression & aggregation methods. Modifying the TPC can be achieved by using directional antennas, location or RSSI-based low power transmission tuning or bit rate per frame adaptation in CDMA-based devices. Consequently, making use of the aforementioned rules efficiently, maximization of the communication time with minimized energy consumption can be achieved not only before the handover (proactive handover) but also after the handover (associating with the most energy efficient network means the device will consume the least amount of energy for wireless access after the handover until the channel condition has changed and the device decides to hand over again). V. EXPECTED POWER CONSUMPTION & USER NOTIFICATION An energy-efficient interface selection approach can be implemented making use of the aforementioned rules. However, in order to ensure the activation of the most energyefficient interface, a tool/scheme that estimates the expected power consumption of each interface/network and associates
with a PoA that is expected to consume the least amount of energy among all PoAs is also required. Consequently, the tool must be responsible of estimating the expected power consumptions of each PoAs deployed in all interfaces one by one. Thus, the tool can compare the expected power consumptions of the current associated PoA and other PoAs in the vicinity and associate with the most energy-efficient interface/network. In a wireless network, a mobile station can be mainly in one of four states: transmission, receiving, idle and doze state. Stations in the transmission state consume the most power, followed by the receiving and idle state. The Power Saving Mode (PSM) disables the wireless network interface during inactive periods. Therefore, mobile stations consume the least power in the doze state. However, applications are mainly implemented to transmit/receive as many frames as possible, and hence they remain active (in one of the transmission, receiving, or idle states) most of the time. Consequently, computation of how much power a station needs to obtain a specific throughput in case of a possible association with available PoAs is important. The amount of expected power consumption of a station can be computed as, ,
, ,
, .
(1)
where Pt(i,j), Pidle(i,j), Pr(i,j) and Pdoze(i,j) are the amount of power consumption of the interface/network i and the traffic type j in the transmitting, idle, receiving and doze state, respectively. tt, tidle, tr and tdoze are the time intervals corresponding to each state. Gathering local and network-related information (such as, channel utilization, application type, signal strength, amount of power consumption in each state, etc.), stations can predict the approximate time interval of each state and compute the expected power consumption of each PoA separately. Consequently, the proposed tool lets stations find a proper PoA that is expected to consume the least amount of energy. The amount of energy saving (Es) can be calculated by subtracting the amount of expected power consumption of the current PoA ( ) from the PoA ( ) that is expected to consume the least amount of energy as follow, ,
.
(2)
Moreover, information of interface switching and the amount of expected energy saving can be shared with users by a notification before the handover execution. This way, users can notice that there is a proper PoA, and they can decide to associate or not by themselves. VI.
FROM THE ACTIONS TO BE TAKEN TO REALITY
Energy-efficient wireless connectivity is in a key role for the ICT. To this end, governments, NGOs and private companies are now in search of energy-efficient opportunities for new services, applications, research and businesses. Well awareness and coordination among public and private sectors on power-aware standards can accelerate energy-efficient technology development and deployment. In this context, this
roadmap aims to serve as a resource and establish an agenda for governments, NGOs, and private companies to contribute to possible energy-efficient interface selection standardization. In line with the aforementioned explanations and in order to address the issue in a global context, we recommend the following actions be taken by governments: (1) Policy development: Governments should define clear strategies and formulate realistic goals for short and long-term periods; (2) Enabling legislation: Governments should provide tax incentives or penalties for the products that supports poweraware interface selection or not, respectively; (3) International negotiation & collaboration: Though countries have different environmental conditions, governments should work together for data exchange and develop a single appropriate standard. (4) Research and education funding: The key to success for energy-efficient interface selection standardization is to fund research and education programs and to link existing resources. The term NGO describes a range of groups, organizations that follow a public interest, rather than commercial interests. NGOs can also design products that will minimize the environmental impacts of consumption. In this context, we recommend the following actions to be taken by NGOs: (1) National standardization: NGOs and private sectors should come together to participate in the development of an energyefficient interface selection guidance and standard; (2) Awareness: Citizens can be educated for the awareness of their own responsibility in sustainable energy consumption. Private sector has both the most to gain and the most to lose from standardizations and regulations. Products that support energy-efficient interface selection process/standard results in user satisfaction as communication time of mobile devices will increase. In contrast, non-energy-aware products will lose the attention in time. Consequently, private companies must have technical know-how to design and develop related standards on their products. They must be transparent and open to NGOs as well. VII. CONCLUSION This paper presents a roadmap for green interface selection standardization over wireless HetNets. Throughout the paper, essential rules (such as, mobile and network assisted handover, resource management, user-preferences, historical information, dynamic channel scanning etc.) of energyefficient interface selection procedure are formulated and described in details. Additionally, a power consumption equation is proposed as a necessary tool that might be used to predict the expected power consumption of each interface. The actions that need to be taken towards standardization from the perspective of governments, NGOs and companies are discussed. Consequently, this paper proposed a roadmap that intends to raise the awareness of energy efficiency in wireless HetNets, and to highlight a green interface selection process where additional standardization is needed.
REFERENCES [1]
[2]
‘Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update 2014–2019 White Paper’, Cisco. [Online]. Available: http://cisco.com/c/en/us/solutions/collateral/service-provider/visualnetworking-index-vni/white_paper_c11-520862.html. [Accessed: 06July-2015]. E. Gustafsson, A. Jonsson, “Always best connected”, IEEE Wireless Communications 10(1): 49–55, 2003.
[3]
S. Zeadally, SU. Khan, N. Chilamkurti, “Energy-efficient networking: past, present, and future”, Journal of Supercomputing, 1093–1118, 2012.
[4]
The Climate Group, Smart 2020, ‘‘Enabling the low carbon economy in the information age’’, 2008. [Online]. Available: http://www.smart2020.org. [Accessed: 26-June-2015].
[5]
R. Kumar, L. Mieritz, ‘‘Conceptualizing green IT and data centre power and cooling issues’’, Gartner research paper, April 2007.
[6]
R. Mahapatra, AD. Domenico, R. Gupta, EC. Strinati, “Green framework for future heterogeneous wireless networks”, Comput. Networks, 57(6): 1518–1528, 2013.
[7]
K., Pentikousis, “In search of energy-efficient mobile networking,” IEEE Commun. Mag., 48(1): 95–103, 2010.
[8]
E.C. Strinati, A. De Domenico, L. Herault, “Green Communications: An Emerging Challenge for Mobile Broadband Communication Networks,” Journal of Green Engineering, Vol. 1, pp. 267–301, 2011.
[9]
Green Touch Initiative, 2012. .
[10] M. Gruber, O. Blume, D. Ferling, D. Zeller, M. Imran, E. Calvanese Strinati, “EARTH-energy aware radio and network technologies”, PIMRC, Tokyo, Japan, pp. 1–5, 2009. [11] C. Han, T. Harrold, S. Armour, I. Krikidis, S. Videv, P. Grant, H. Haas, J. Thompson, I. Ku, C. Wang, et al., “Green radio: radio techniques to enable energy-efficient wireless networks”, IEEE Communications Magazine, Vol. 49, pp. 46–54, 2011. [12] G. P. Perrucci, and F. H. P. Fitzek, J. Widmer, “Survey on Energy Consumption Entities on the Smartphone Platform,” Vehicular Technology Conference, 2011. [13] M.F. Tuysuz, ‘‘An energy-efficient QoS-based network selection scheme over heterogeneous WLAN-----3G networks’’, Computer Networks, Vol. 75, pp. 113---133, 2014. [14] IEEE802.21 Standard, “Local and Metropolitan Area Networks — Part 21: Media Independent Handover Services,” Jan. 2009. [15] N. Vulic, S.M. Heemstra de Groot, I.G.M.M. Niemegeers, “Vertical handovers among different wireless technologies in a UMTS radio access-based integrated architecture”, Computer Networks, 55(7): 1533–1548, 2011. [16] ETSI, “Architecture enhancements for non-3GPP accesses, (3GPP TS 23.402 version 10.3.0 Release 10),” ETSI, Technical Standard TS 123 402 - V10.3.0, Mar. 2011. [17] JMR. Castillo, “Energy-Efficient Vertical Handovers”, Ph.D. dissertation, School of Information and Communication Technology, KTH Royal Institute of Technology, Sweden, 2013. [18] IEEE standard 802.11u , “Part 11: wireless LAN medium access control (MAC) and physical layer (PHY) specifications – amendment 9 interworking with external networks”, 2011. [19] Wi-Fi Alliance, Hotspot 2.0 Technical Specification v1.0.0, 2012. [20] R. Trestian, Q-T. Vien, P. Shah, and G. Mapp, “Exploring Energy Consumption Issues for Multimedia Streaming in LTE HetNet Small Cells”, IEEE Local Comupter Networks, 2015. [21] Y.C. Tseng., C.S.Hsu., T.Y. Hsieh., “Power-Saving Protocols for IEEE 802.11 Based Multi-Hop Ad Hoc Networks”, IEEE Computer Networks, 43(3): 317---337, 2002.
