Boumediene v. Bush: Another Chapter in the Court’s Jurisprudence on Civil Liberties at Guantanamo Bay

A recent surge in the usage of instant messaging (IM) applications on mobile devices has brought the energy efficiency of these applications into focus of attention. Although IM applications are changing the message communication landscape, this work illustrates that the current versions of IM applications differ vastly in energy consumption when using the third generation (3G) cellular communication. This paper shows the interdependency between energy consumption and IM data patterns in this context. We analyse the user interaction pattern using a IM dataset, consisting of 1043370 messages collected from 51 mobile users. Based on the usage characteristics, we propose a message bundling technique that aggregates consecutive messages over time, reducing the energy consumption with a trade-off against latency. The results show that message bundling can save up to 43% in energy consumption while still maintaining the conversation function. Finally, the energy cost of a common functionality used in IM applications that informs that the user is currently typing a response, so called typing notification, is evaluated showing an energy increase ranging from 40-104%

Watts2Share: Energy-Aware Traffic Consolidation

Energy consumption is becoming the Achilles' heel of the mobile user quality of experience partly due to undisciplined use of the cellular (3G) transmissions by applications. The operator infrastructure is typically configured for peak performance, whereas during periods of underutilisation the handsets pay the price by staying in high energy states even if each application only uses a fraction of the maximum available bandwidth. In this paper we promote a bi-radio scenario where instead of independently using own cellular connections, several users share a single cellular link offered by one member of a coalition (a rotating aggregator). We present Watts2Share, an architecture for energy-aware traffic consolidation whereby group members' data flows transmitted through a second radio (e.g., WiFi) are aggregated by the aggregator and retransmitted through the cellular link. Through careful and repeatable studies we demonstrate that this scheme saves up to 68% of the total transmission energy in handsets compared to a pure 3G scenario. The studies are based on a wide range of real traffic traces and real cellular operator settings, and further illustrate that this scheme reduces the overall energy by reducing the signalling overhead, as well as extending the lifetime of all handsets

Energy Modelling and Fairness for Efficient Mobile Communication

Energy consumption and its management have been clearly identified as a challenge in computing and communication system design, where energy economy is obviously of paramount importance for battery powered devices. This thesis addresses the energy efficiency of mobile communication at the user end in the context of cellular networks. We argue that energy efficiency starts by energy awareness and propose EnergyBox, a parametrised tool that enables accurate and repeatable energy quantification at the user end using real data traffic traces as input. EnergyBox offers an abstraction of the underlying states for operation of the wireless interfaces and allows to estimate the energy consumption for different operator settings and device characteristics. The tool is used throughout the thesis to quantify and reveal inefficient data communication patterns of widely used mobile applications. We consider two different perspectives in the search of energy-efficient solutions. From the application perspective, we show that systematically quantifying the energy consumption of design choices (e.g., communication patterns, protocols, and data formats) contributes to a significantly smaller energy footprint. From the system perspective, we devise a cross-layer solution that schedules packet transmissions based on the knowledge of the network parameters that impact the energy consumption of the handset. These attempts show that application level decisions require a better understanding of possible energy apportionment policies at system level. Finally, we study the generic problem of determining the contribution of an entity (e.g., application) to the total energy consumption of a given system (e.g., mobile device). We compare the state-of-the-art policies in terms of fairness leveraging cooperative game theory and analyse their required information and computational complexity. We show that providing incentives to reduce the total energy consumption of the system (as part of fairness) is tightly coupled to the policy selection. Our study provides guidelines to select an appropriate policy depending on the characteristics of the system.

Implementation of a manycast protocol for intermittently connected mobile ad hoc networks in disaster areas

Nowadays, the use of mobile phones and other wireless devices has become an indispensable part of daily life. However, the focus of wireless communication is on infrastructure-based networks, making them prone to service outage if for any reason the infrastructure is overloaded or there is no network coverage. This is the case in a disaster area, where the infrastructure that supports the communication may be destroyed or could become useless. Different approaches to complement the exchange of information in these scenarios are emerging as research results. This thesis concerns Random-Walk Gossip (RWG), which is a protocol to disseminate information in disaster areas. RWG is a many-cast protocol for intermittently connected mobile ad hoc networks. The more people can communicate, the more chances of success there are. Therefore, it is useful to investigate the possibility of implementing such protocols on commodity devices. Since Symbian is currently the most widespread mobile phone operating system, this master's thesis presents the implementation of the protocol in that platform. The protocol is also implemented in Linux and Mac OS X in order to provide heterogeneity. Finally, some aspects of the performance of the protocol in different devices are analyzed, studying the CPU load, memory consumption, radio range, energy consumption and response time of different devices using the protocol. The studies show that the use of the RWG protocol in both laptops and handheld devices is viable

Exploiting Energy Awareness in Mobile Communication

Although evolving mobile technologies bring millions of users closer to the vision of information anywhere-anytime, device battery depletions hamper the quality of experience to a great extent. The massive explosion of mobile applications with the ensuing data exchange over the cellular infrastructure is not only a blessing to the mobile user, but also has a price in terms of rapid discharge of the device battery. Wireless communication is a large contributor to the energy consumption. Thus, the current call for energy economy in mobile devices poses the challenge of reducing the energy consumption of wireless data transmissions at the user end by developing energy-efficient communication. This thesis addresses the energy efficiency of data transmission at the user end in the context of cellular networks. We argue that the design of energy-efficient solutions starts by energy awareness and propose EnergyBox, a parametrised tool that enables accurate and repeatable energy quantification at the user end using real data traffic traces as input. EnergyBox abstracts the underlying states for operation of the wireless interfaces and allows to estimate the energy consumption for different operator settings and device characteristics. Next, we devise an energy-efficient algorithm that schedules the packet transmissions at the user end based on the knowledge of the network parameters that impact the handset energy consumption. The solution focuses on the characteristics of a given traffic class with the lowest quality of service requirements. The cost of running the solution itself is studied showing that the proposed cross-layer scheduler uses a small amount of energy to significantly extend the battery lifetime at the cost of some added latency.  Finally, the benefit of employing EnergyBox to systematically study the different design choices that developers face with respect to data transmissions of applications is shown in the context of location sharing services and instant messaging applications. The results show that quantifying energy consumption of communication patterns, protocols, and data formats can aid the design of tailor-made solutions with a significantly smaller energy footprint.

EnergyBox : A Trace-driven Tool for Data Transmission Energy Consumption Studies

Although evolving mobile technologies bring millions of users closer to the vision of information anywhere-anytime, device battery depletions hamper the quality of experience to a great extent. We argue that the design of energy-efficient solutions starts by energy-awareness and propose EnergyBox, a tool that provides accurate and repeatable energy consumption studies for 3G and WiFi transmissions at the user end. We recognize that the energy consumption of data transmission is highly dependable on the traffic pattern, and provide the means for trace-based iterative packet-driven simulation to derive the operation states of wireless interfaces. The strength of EnergyBox is that it allows to modularly set the 3G network parameters specified at operator level, the adaptive power save mode mechanism for a WiFi device, and the different power levels of the operation states for different handheld devices. EnergyBox enables efficient energy consumption studies using real data, which complements the device-dependent laborious physical power measurements. Using real application transmission traces, we have validated EnergyBox showing an accuracy range of 94-99% for 3G and 93-99% for WiFi compared to the real measured energy consumption by a 3G modem and a smartphone with WiFi

Watts2Share : Energy-Aware Traffic Consolidation

Energy consumption is becoming the Achilles' heel of the mobile user quality of experience partly due to undisciplined use of the cellular (3G) transmissions by applications. The operator infrastructure is typically configured for peak performance, whereas during periods of underutilisation the handsets pay the price by staying in high energy states even if each application only uses a fraction of the maximum available bandwidth. In this paper we promote a bi-radio scenario where instead of independently using own cellular connections, several users share a single cellular link offered by one member of a coalition (a rotating aggregator). We present Watts2Share, an architecture for energy-aware traffic consolidation whereby group members' data flows transmitted through a second radio (e.g., WiFi) are aggregated by the aggregator and retransmitted through the cellular link. Through careful and repeatable studies we demonstrate that this scheme saves up to 68% of the total transmission energy in handsets compared to a pure 3G scenario. The studies are based on a wide range of real traffic traces and real cellular operator settings, and further illustrate that this scheme reduces the overall energy by reducing the signalling overhead, as well as extending the lifetime of all handsets

When Mice Consume Like Elephants: Instant Messaging Applications

A recent surge in the usage of instant messaging (IM) applications on mobile devices has brought the energy efficiency of these applications into focus of attention. Although IM applications are changing the message communication landscape, this work illustrates that the current versions of IM applications differ vastly in energy consumption when using the third generation (3G) cellular communication. This paper shows the interdependency between energy consumption and IM data patterns in this context. We analyse the user interaction pattern using a IM dataset, consisting of 1043370 messages collected from 51 mobile users. Based on the usage characteristics, we propose a message bundling technique that aggregates consecutive messages over time, reducing the energy consumption with a trade-off against latency. The results show that message bundling can save up to 43% in energy consumption while still maintaining the conversation function. Finally, the energy cost of a common functionality used in IM applications that informs that the user is currently typing a response, so called typing notification, is evaluated showing an energy increase ranging from 40-104%

Fairness and Incentive Considerations in Energy Apportionment Policies

The energy consumption of a system is determined by the system component usage patterns and interactions between the coexisting entities and resources. Energy accounting plays an essential role to reveal the contribution of each entity to the total consumption and for energy management. Unfortunately, energy accounting inherits the apportionment problem of accounting in general, which does not have a general single best solution. In this paper we leverage cooperative game theory commonly used in cost allocation problems to study the energy apportionment problem, i.e., the problem of prescribing the actual energy consumption of a system to the consuming entities (e.g., applications, processes or users of the system). We identify five relevant fairness properties for energy apportionment and present a detailed categorisation and analysis of eight previously proposed energy apportionment policies from different fields in computer and communication systems. In addition, we propose two novel energy apportionment policies based on cooperative game theory which provide strong fairness notion and a rich incentive structure. Our comparative analysis in terms of the identified five fairness properties as well as information requirement and computational complexity shows that there is a trade-off between fairness and the other evaluation criteria. We provide guidelines to select an energy apportionment policy depending on the purpose of the apportionment and the characteristics of the system

EnergyBox: Disclosing the wireless transmission energy cost for mobile devices

While evolving mobile technologies bring millions of users closer to the vision of information anywhere-anytime, device battery depletions still hamper the quality of experience to a great extent. The energy consumption of data transmission is highly dependent on the traffic pattern, and we argue that designing energy efficient data transmissions starts by energy awareness. Our work proposes EnergyBox, a parametrised tool that facilitates accurate and repeatable energy consumption studies for 3G and WiFi transmissions at the user end using real traffic data. The tool takes as input the parameters of a network operator and the power draw for a given mobile device in the 3G and WiFi transmission states. It outputs an estimate of the consumed energy for a given packet trace, either synthetic or captured in a device using real applications. Using nine different applications with different data patterns the versatility and accuracy of the tool was evaluated. The evaluation was carried out for a modern and popular smartphone in the WiFi setting, a specific mobile broadband module for the 3G setting, and within the operating environment of a major mobile operator in Sweden. A comparison with real power traces indicates that EnergyBox is a valuable tool for repeatable and convenient studies. It exhibits an accuracy of 94–99% for 3G, and 95–99% for WiFi given the studied applications’ traces. Next the tool was deployed in a use case where a location sharing application was ran on top of two alternative application layer protocols (HTTP and MQTT) and with two different data exchange formats (JSON and Base64). The illustrative use case helped to identify the appropriateness of the pull and push strategies in sharing location data, and the benefit of EnergyBox in characterising where the breaking point lies for preferring one or the other protocol, under which network load, or exchange data format