From: Self organization based energy management techniques in mobile complex networks: a review
Energy management technique | Implementation | Evaluated YES/NO | Evaluation setup/ methodology | Energy consumption | |
---|---|---|---|---|---|
Operating Systems | |||||
Cinder (Roy et al. 2011) | Abstractions are implemented in the Cinder kernel, which runs on AMD64, i386, SPARC, and ARM architectures. It is freely available on Internet | Yes | HTC Dream (Google G1), based on the Qualcomm MSM7201A chipset | 12.5% total system power reduction over the 20min experiment | |
ErdOS (Vallina-Rodriguez 2011) | Prototype is implemented as an extension of the Android OS | No | N/A | Authors claim that it improves the battery capacity of smart phones by managing resources proactively | |
CondOS (Zhao 2011) | N/A | No | N/A | Authors claim that it provides several opportunities for energy reduction, such as shared dataflow processing, dataflow-to-hardware mapping, and principled flow degradation | |
CONTEXTO (Schirmer and Bertel 2014) | Prototype is currently available as an iOS framework | Yes | Apple iPhone 4, 4S, and 5 | Provides energy-awareness to developers of context-aware applications | |
AURA (Pasricha et al. 2015) | Prototype is implemented as a middleware on two android based smart phones | Yes | HTC Dream and Nexus One | Can achieve up to 29% energy savings as compared to the baseline device manager & it’s 5 times more energy efficient then previous approaches | |
Software Solutions | |||||
Energy-efficient Wireless Interfaces | Catnap (Dogar and Steenkiste 2010) | Prototyped in C for the Linux environment | Yes | Nokia N810 and IBM Thinkpad T60 both supporting 802.11 PSM | Allows the NIC to sleep for around 40% of the time for a 10MB transfer while 70% of the time for a 5MB transfer. Improves battery capacity up to 2-5x for real devices like Thinkpad T60 & Nokia N810 |
NAPman (Rozner et al., 2010) | Prototyped using the MadWifi v0.9.4 driver for Atheros-based WiFi cards on the Linux platform | Yes | HP iPAQ hw6945, iPhone 3GS, gPhone HTC Magic and HTC Tilt 8900 | Under varied settings of background traffic, it improves the energy savings on a smartphone by up to 70% while ensuring fairness | |
Bartendr (Schulman et al. 2010) | N/A | Yes | 4 cellular networks across 2 metropolitan areas, one in US & the other in India, and spans 3G networks based on both EVDO & HSDPA | Significant energy savings of up to 10% for email sync and up to 60% for on-demand streaming | |
SALSA (Ra et al. 2010) | Implemented SALSA algorithm in Urban Tomography system which runs on the Nokia N95 smartphone, having 802.11b/g WiFi interface, 3G/EDGE, a 2GB micro-SD card, & supports 640x480-resolution video recording capability | Yes | Nokia N95 and Android G1 | Closer to an empirically determined optimal than any other alternatives compared with it, and, can save 10-40% of battery for some workloads | |
PhoneJoule (Liu et al. 2013) | Prototype is implemented using java and Eclipse integrated with Android SDK & ADT. It can work on all smartphones which support Android OS 2.2 or later versions | Yes | ZTE v880 smartphone which supports Android OS 2.2 and SEMO to measure power consumption | Very effective for energy saving in smartphones and makes it very convenient for users to manage battery usage of their smartphones | |
PerES (Cui et al., 2013) | Implemented as a traffic management application by utilizing IPTABLES (a system tool in Android) | Yes | Google Nexus S and Monsoon Power Monitor device | Better than peer schemes, TailEnder & SALSA. Using 821 million traffic flows collected from commercial cellular carrier, it can achieve on average 32% to 56% energy savings with different levels of user experience | |
Energy-efficient Sensors | A-loc (Lin 2010) | Prototype is implemented on an Android G1 phone | Yes | Android G1 and AT&T Tilt phones, on paths that include indoor and outdoor locations, using war driving data from Microsoft & Google | Saves significant amount of energy and also improves the accuracy |
Adaptive location-sensing framework (Zhuang et al., 2010) | Design principles are implemented as a middleware on G1 Android Phone with OS version 1.5 Cupcake, by modifying the Application Framework | Yes | G1 Android Developer Phone (ADP) | Minimize the usage of the energy-consuming GPS up to 98% and improve battery life by up to 75% | |
RAPS (Paek et al., 2010) | Prototype is implemented in Symbian C++ for the Symbian S60 3rd FP1 devices | Yes | Nokia N95-3 smartphone, with GPS, accelerometer, Bluetooth, WiFi and 3G/EDGE interfaces, & 2GB micro-SD card | Can increase phone battery by more than a factor of 3.8 as compared to the approach where GPS is always on | |
Bayesian Networks (Yi and Cho 2012) | Proposed context-aware system for GPS has prototyped as an application in Android platform | Yes | LG SU-660 with Android OS 2.2 version | Active person and inactive person can save energy of about 5% and 3% per hour, respectively | |
Jigsaw (Lu et al. 2010) | Proposed continues sensing engine has implemented on two smartphone platforms, Nokia N95 & Apple iPhone, as background service and library, respectively | Yes | Nokia N95 and Apple iPhone | Authors claim that Jigsaw is capable of performing long-term energy efficient GPS tracking without sacrificing the accuracy. However, the paper lacks clear performance evaluation results | |
WheelLoc (Wang et al. 2013) | Implemented as a continuous background system service on NexusOne phones running Android 2.3 | Yes | NexusOne phones with Android OS 2.3 version | Can return a location estimate within 40ms with an accuracy about 40 meters, consumes only 240mW energy, & effectively strikes a better energy-accuracy tradeoff than GPS duty-cycling | |
Energy-efficient Computation-offloading | MAUI (Cuervo and Balasubramanian 2010) | Prototype is implemented on HTC Fuze smartphone running Windows Mobile 6.5 with .Net Compact Framework v3.5 | Yes | HTC Fuze smartphone running Windows Mobile 6.5 with .Net Compact Framework v3.5 and for MAUI server, dual-core desktop with 3GHZ & 4GB RAM running Win 7 | For 4 applications running on Windows Mobile phones, it can achieve energy conservation of up to one order of magnitude |
Cuckoo (Kemp et al., 2012) | Integrates with the popular open source Android framework and the Eclipse development tool | Yes | 2 real world apps that contain heavy weight computation, eyeDentify and PhotoShoot | With little effort computation off-loading can be enabled for object recognition and gaming app, using the Cuckoo framework | |
Synergy (Kharb et al., Kharbanda et al. 2012) | Prototype implementation is developed for the Android operating system | Yes | 2 compute intensive apps – image smoothing & video processing running on Google Nexus S with Android OS 2.2 version and PowerTutor | Can save up to 30.6% of the system battery with less than 5% latency penalty | |
MADNet (Ding et al., 2013) | Prototype is implemented on Nokia N900 smartphones | Yes | Nokia N900, Nokia E71 and Samsung Nexus S. Energy Profiler application and Monsoon Power Monitor | Can achieve more than 80% energy saving | |
Self learning off-loading scheme (Arora 2014) | N/A | No | N/A | Authors claim that enabling the off-loading system to self learn makes it more reliable, fast and energy efficient | |
Battery Management Mobile Applications | Android and iOS platform | Yes | Android and iOS | It allows users to quickly look up battery status as well as track down what applications are draining battery life. It also helps to charge the device healthily with 3 Stage Charging system and it can extend the battery life up to 50% | |
Android | Yes | Android and AV-TEST | Multifunctional application which works like a cleaner and as an antivirus at the same time. It can boosts mobile applications by almost 32% and it also protects the device from unwanted malware & spyware | ||
Hardware solutions | |||||
Little Rock (Priyantha and Lymberopoulos 2011) | Integrated Little Rock into an actual prototyping phone | Yes | Pedometer app while running on the phone, on Little Rock as well as on a hybrid architecture that includes the phone with an embedded Little Rock board | For a pedometer application, the energy savings by running with Little Rock is three orders of magnitude compared to the normal approaches | |
MobileHub (Haichen et al., 2014) | Prototyped with a sensor hub comprised of an 8-bit AVR micro-controller attached to sensors, and by extending the Android OS to use this sensor hub | Yes | Galaxy Nexus phones with Android OS 4.2.2 version | For three applications downloaded from the Android marketplace, it can improve power consumption by up to 83%, with no effort from the developer |