New Channel Allocation Techniques for Power Efficient WiFi Networks

Transcription

1 ew Channel Alloation Tehniques for Power Effiient WiFi etworks V. Miliotis, A. Apostolaras, T. Korakis, Z. Tao and L. Tassiulas Computer & Communiations Engineering Dept. University of Thessaly Centre for Researh & Tehnology Hellas Volos, Greee Mitsubishi Eletri Laboratories Researh, Priniple Tehnial Staff Cambrdige, Massahusetts, USA {vmiliotis, apaposto, korakis, Abstrat Energy effiieny beomes evergreen than ever before. Over the last few years a signifiant researh in wireless ommuniations, aiming to enhane ommuniations effiieny subjet to onstraint of power onsumption, has given rise to optimization tehniques of power ontrol and management in wireless networks. Although the initial target was the utilization of resoures in order to exploit ommuniations servies, the benefits of this effort, underlying the green perspetive, are now opening eyes out to researh ommunity for a more green matter of onsiene in use of ommuniation equipment and devies. Towards this diretion and affeted by a green sensitivity in terms of wasting useful resoures, we propose a system model for infrastruture WiFi networks aiming to redue the onsumed power, by introduing a sheme for hannel alloation to Wireless LAs under energy onserving riteria. I. ITRODUCTIO Green Tehnologies brings the promise of providing signifiant improvements on reduing global energy onsumption. On ommuniations area, green tehnologies are mainly keen on reduing power onsumption on portable devies, sine a ritial issue for almost all kinds of suh devies is power saving. Beause of the battery-dependene, portable devies will beome useless if there is an unrestrained power onsumption. Battery power is a limited resoure, and it is expeted that battery tehnology is not likely to progress as fast as omputing and ommuniation tehnologies do. Hene, effiient ways of lengthening batteries lifetime is an important issue, on optimizing ommuniations. Power Control tehniques aim to redue energy onsumption in a way that a sender transmits information and onsumes only the required power for eah transmission, that depends on the length (buffer baklog length) of the transmitted information or the hannel quality. In ases of baklog driven power ontrol, on eah time-slot unit a alulation for the transmitted power is being performed. On the long term, a signifiant power onsumption redue is ahieved sine transmissions are being emitted, proportional to the information length energy amount and the realulation for the power settings is frequently evaluated. Moreover, by adopting tehniques for reasonable power transmissions would affet the ommuniations quality environment, sine the noise realized by the nearby Aess Points and Stations would be mitigated. The inreased number of networks in ontemporary urban environments and the utilization of the limited frequeny spetrum auses many networks to operate on shared hannels. If all Stations and Aess Points redue their power transmission level to a minimum quality threshold that does not adversely affet the link quality ommuniation among them, that would improve immediately ommuniation quality on nearby networks in terms of diminished neighborhood interferene. While h [1] amendment provides for a DFS mehanism in WLAs, its purpose was initially to avoid ohannel operation with radar systems and to insure uniform utilization of available hannels in the 5GHz band. This amendment was mainly introdued for European Countries, where radio regulations prohibit the utilization of 5 GHz band in loations where there exist radar operation. The Transmit Power Control (TPC) mehanism desribed in the same amendment was introdued, in order for WLAs to operate omplying with the European regulatory maximum transmit power for eah allowed hannel and to redue interferene with satellite servies. However, in most ases of wireless tehnologies it is required to ahieve throughput improvement while also reduing energy onsumption due to limited power resoures that also bring high ost. In a wireless network, throughput is diretly dependent on the hannel quality. In partiular, more often than not, there may be a mismath in the quality of the link from the AP (Aess Point) and its STAs (stations) due to unrestrained external interferene. This mismath leads us to adopt more effiient ways on hannel seletion: (a) for ahieving higher throughput and (b) for reduing power onsumption sine paket ongestion implies augmented amount of retransmissions. In this paper, we propose a Dynami Frequeny Seletion (DFS) algorithm, that takes into aount the network s traffi and the ontention free period of time, pereived by all STAs and the AP of a WLA and swithes to the hannel that will provoke less frame retransmissions. Continued on the paper below, a related work analysis is reported on Setion II, on Setion III our system model is presented, on setion IV the experimentation platform that we used is desribed, on Setion V experimentation results on real

2 ase senarios are presented and on setion V we finalize with onlusions. II. RELATED WORK In the last years, there has been a wide spread in the usage of wireless LAs. Due to this degree of dissemination of WiFi tehnology, large researh effort has been devoted to the improvement of medium aess ontrol protools aiming to minimize the transmission delay and to maximize throughput. Power onsumption has only later beome an issue of researh interest. The initial perspetive was to extend the battery life of mobile devies in order to keep the network alive for longer duration [2], [3], [4]. ow, the aspet of green wireless tehnology has beome a hot topi and through sustainable development it aims to preserve the environmental resoures by minimization of power onsumption. Towards this onept, the researh ativity regarding power effiieny in wireless networks is divided in two main fields. The first refers to ad-ho wireless networks and the seond to infrastruture wireless LAs. In ad-ho networks, the power management is based on traffi indiation messages. The stations of an independent network use announement traffi indiation messages (ATIMs), to preempt other stations from sleeping. All stations in an Independent Basi Servie Set (IBSS) listen for ATIM frames during speified periods after Beaon transmissions. Stations that do not reeive ATIM frames are free to onserve power entering power saving mode. Aording to the standard [5], no stations are permitted to power down their wireless interfaes during the ATIM window. To monitor the entire ATIM window, stations wake up before the target Beaon transmission. There are four possible situations. The station may have transmitted an ATIM, reeived an ATIM, neither transmitted nor reeived and both transmitted and reeived an ATIM. A station is permitted to sleep only if it neither transmitted nor reeived ATIM frames. A sheme in whih a station an vary the duration of awake-state to adapt the traffi to the network is proposed in [6]. Oppose to the fixed value of ATIM Window and Beaon Interval mentioned in the standard, the proposed sheme splits the ATIM Window into two parts, the Earlier Time Slot (ETS) and the Later Time Slot (LTS). If the transmitter issuing a Beaon has data pakets to send in its buffer, it tries to transmit the Beaon in the ETS, otherwise it tries to delay it till the LTS. If no Beaon transmission takes plae during ETS, all nodes assume that no buffered data exist and hange their state to sleep mode right after reeiving a Beaon in the LTS. The optimal ETS and LTS duration is also explored. The proposed protool in [7] addresses the problem of power onsumption by trying to minimize overhearing, over transmission and paket ollisions by using a 2-hop reeiver entri message passing mehanism. This mehanism mitigates the hidden terminal and the exposed terminal in multi-hop environments. In order to ahieve this goal, during the ATIM window, the sender node transfers an ATIM Request paket to the reeiver node, whih inludes the time duration for the data transmission. The reeiver node transfers an ATIM ACK paket to the sender node, inluding again the time duration of the transmission. This ontrol paket is transferred to all nodes having logial 2-hop distane from the reeiver node. By mitigating the hidden and the exposed terminal problems, less retransmission is provoked and onsequently power onsumption is redued. In infrastruture networks, aording to the standard, power onservation is ahieved by means of buffering traffi at the AP. As all traffi must go through the AP and simultaneously assuming that it has aess to ontinuous power, it makes an ideal loation for buffering traffi and plays a key role in power management on infrastruture networks. The power management desribed in the standard onsists of two elements, the Traffi Indiation Map (TIM) and the Power Saving Poll (PS-Poll). The AP periodially assembles TIM, whih is used to inform stations for whih frames are buffered. TIM is transmitted in Beaon frames and refers to uniast frames. Buffered broadast and multiast frames are announed in Delivery Traffi Indiation Map (DTIM). At a fixed number of Beaon intervals DTIM is transmitted in Beaon frames instead of TIM. A mobile STA wakes up, following the Listen Interval parameter agreed during the assoiation proedure, to reeive the TIM. If the AP has buffered traffi on its behalf, it transmits a PS-Poll frame to retrieve buffered frames. One buffered traffi is delivered, the STA an resume sleeping. There is several reported work in literature on power effiieny for infrastruture networks. In [8], power effiieny is expressed as the transmitted traffi per unit of energy. The proposed power optimization sheme is based on a ross layer seletion of appropriate power level and modulation. An analogous sheme, that ombines Transmit Power Control (TPC) with PHY rate seletion, is presented in [9] for the point oordination funtion (PCF) operation of wireless LAs. Based on the fat that low rate STAs, when transmitting, oblige high rate STAs, willing to transmit, to onsume onsiderable amount of energy listening the hannel, a ooperative sheme is proposed in [10]. In this sheme, low rate STAs are alloted, unequal to other STAs, with less hannel aess time for data ommuniation with the ompensation of ommuniating with the AP through a high rate path. This way high rate STAs funtion as relays between the AP and the low rate STAs, establishing this high rate path. In our work, we propose hannel alloation tehniques for infrastruture wireless networks, aiming to mitigate the energy onsumption of the wireless LA. The h amendment, where Dynami Frequeny Seletion (DFS) for networks was defined, mainly for avoidane of ohannel operation with Radars and uniform utilization of available hannels, boosted the researh ativity on this area. Both distributed [11], [12] and entralized [13], [14] algorithms for dynami hannel alloation have been proposed, but less attention has been given on hannel alloation with energy onserving riteria. With our work we give a new perspetive in this field, introduing new hannel alloation tehniques for power effiieny in WiFi networks.

3 max λ 0 + λ i a i + λ 0 λ 0 + λ0 λ a 0 i (4) Fig. 1. Monitoring Window Intervals. For every period T m we symbolize the downlink and the uplink mean traffi ratio as d r and u r respetively. amely: III. SYSTEM MODEL We onsider an IEEE based WLA, whih onsists of one aess point (AP) and mobile stations (STAs) and it is plaed among other WLAs. This senario is frequently met in dense urban environments, where in every home and enterprise there is a wireless AP, reating an overused wireless environment. In our model we introdue a periodial monitoring window, during whih, all STAs and the AP that omprise the WLA, monitor their operating hannels for equal duration. We define as T m the period between the beginning of every monitoring window and T w the duration of this time window, whih is a silent period for the WLA. During T w every STA and the AP monitor their operating frequenies for equal period of time t. During t, the reeived power level at the wireless etwork Interfae Card (IC) is measured and the time that the sensed power is below a prespeified threshold is aptured. We define this aptured time a i as ontention free time fator of the hannel, {1, 2,...,11} deteted by STA i, i {1, 2,...,}. a i = t free t (1) The ontention free time deteted by the AP is symbolized as a 0. In the end of the monitoring window T w, every STA sends its measurements of ontention free time fators to the AP. During T m, the AP keeps trak of the mean downlink traffi for every STA i, equal to λ i, and for the total inoming uplink traffi from all stations of the WLA, equal to λ 0. Consequently, in order to selet the hannel that will lead the WLA to meet less ontention for the downlink ase, we need to find the hannel, that maximizes the following quantity: max λ i a i (2) For the uplink ase, aiming again to fae less ontention with the neighboring WLAs, we want to maximize the following quantity: max λ0 a 0 In order to hoose the best hannel for the joint downlink and uplink ase we assign weights to quantities (2) and (3), proportional to the downlink and uplink traffi ratio to the total traffi of the WLA. In this way, we formulate our utility funtion as follows: (3) and d r = u r = λ 0 + (5) λ 0 λ 0 + (6) Combining equations (5) and (6) with the quantity (4) we an rewrite our utility funtion as follows: max d r λ i a i + u r λ0 a 0 (7) In our implementation we ompare our proposed model with a stati weighted model where d r = 1 2 and u r = 1 2 that hooses the hannel of operation, without onsidering the traffi ratios, aording to the following utility funtion: 1 max a i a 0 (8) as well as with the ase where only the APs measurements are onsidered. In this ase the utility funtion is: max (a 0) (9) Through experimentation on ITOS testbed [16], we prove the superiority of our proposed sheme ompared to (8) and (9). IV. ITOS WIRELESS TESTBED In order to evaluate the performane and study the behavior of the DFS sheme that we have designed, we used a large sale programmable wireless testbed of heterogeneous wireless nodes. Moving one step further than analysis/simulation, implementation of algorithm in a real wireless platform, would provide results from real world settings. Hene, evaluation and justifiation of the DFS algorithm proposed was tested on ITOS wireless testbed. ITOS (etwork Implementation Testbed for using Open Soure platforms) is a wireless testbed that is designed to ahieve reproduibility of experimentation, while also supporting evaluation of protools and appliations in real world settings. ITOS onsists of nodes based on ommerial WiFi ards and Linux based open soure platforms. It is remotely aessible and supports 15 wireless nodes outdoor loated in a non-rf-isolated environment. Users an perform their experiments by reserving slies (nodes, frequeny spetrum)

4 Algorithm 1 DFS Require: TIME := K T m, K Ensure: FREQUECY SELECTIO 1: while TIME <K T m + T w do 2: for {1,...,11} do 3: for i = {0,...,} do 4: CALCULATE a i 5: end for 6: end for 7: for i = {1,...,} do 8: SED a i TO ACCESS POIT // This ode blok refers to (7) and (8) only. 9: end for 10: ACCESS POIT SELECTS arg CHAEL THAT MAXIMIZES (7), (8) OR (9) 11: WLA SWITCHES O EW CHAEL 12: end while AP 50% 30% 10% 10% ST A1 ST A2 Red APs represent interfering WLAs Fig. 2. Experiment Traffi Setup. of the testbed through ITOS sheduler, that together with OMF[17] management framework supports ease of use for experimentation and ode development. V. IMPLEMETATIO DETAILS In order to evaluate our proposed model, we implemented it, together with the stati weighted model and the model in whih the deisions are made, based only on the APs measurements, using the MadWifi open soure driver [19]. For the implementation of our algorithm, we modified the driver adding a periodial monitoring window. During this monitoring window, every STA and the AP take measurements of the ontention free time fator of every hannel, for equal duration. We also added the generation of uniast frame transmission, so as to give to STAs the funtionality of transmitting their measurements to the AP at the end of the monitoring window. As soon as the measurements are gathered at the AP, a funtion that alulates the best hannel aording to (7) is invoked and the WLA hanges its operating hannel to the new one. In order to ompare our algorithm with other shemes, we also implemented their funtionality on MadWifi aording to (8) and (9) as we have already desribed on previous setion. The evaluation of the performane of our modified MadWifi driver was exeuted on the ITOS wireless testbed [15]. We used one wireless node of the testbed as AP, and two as STAs. As ITOS testbed is a non-isolated wireless testbed we were able to onfront a rih interferene wireless environment for the implementation of our algorithm. More partiularly, during the experimentation proess we observed the existene of more than 9 interfering APs operating randomly on different hannels. This fat gave us a prolifi setting to prove that our Dynami Frequeny Seletion algorithm is more energy effiient than the two others we mentioned above. Hene, our proposed model presents a greener WiFi operation. A. Algorithm Here, we give a brief pseudoode desription of the implemented algorithm, that leads the WLA to swith to the best hannel aording to metris aquired by the evaluation of (7), (8), (9). We denote K the disrete monitoring time intervals. VI. EXPERIMETATIO EVALUATIO The performane of our proposed model and the omparison with the other two stated models was evaluated with experiments in ITOS wireless testbed, on the 11 available hannels of g. We evaluated the energy onsumption of every one of these models, for a WLA operating in a real environment, regarding the interferene that it suffered from. The total traffi between the AP and the two assoiated stations was 550 Mbytes and the transmission rate at 24 Mbps. We generated typial traffi in our WLA transmitting 30% of the total traffi from the AP to STA1, 50% of the total traffi from the AP to STA2 and 20% to the uplink, equally generated from eah station to the AP as depited in Fig. 2. We used iperf [20], in order to reate UDP traffi and MadWifi athstats to take measurements of the retransmitted frames. UDP traffi does not provide Transport Layer retransmission like TCP and thus we were able to measure lean MAC Layer frame retransmissions, provoked by PHY Layer ollisions. The energy effiieny of our Dynami Frequeny Seletion model is justified ompared to the Stati Weighted and the AP measurement based model by means of retransmission perentage of the total UDP traffi generated frames. In our model only 5.6% of the total traffi was retransmitted, while in the seond and the third model the retransmission perentage was 8.9% and 13.2% respetively. Hene, our DFS model proves its superiority regarding the green aspet of WiFi infrastruture networks, as presented in Fig. 3.a

5 Our Sheme Stati Weighted AP Based Our Sheme Stati Weighted AP Based Our Sheme Stati Weigted AP Based Our Sheme Stati Weigted AP Based (a) Frame Retransmission Perentage. (b) Power Consumption Perentage. 0 Fig. 3. Experimental Results (Comparisons are made to the worst ase). Taking into aount an AP based measurements deision model and power onsumption of the Atheros [21] hipset AR5212, with whih ITOS wireless testbed nodes are equipped, we alulated the amount of energy onsumption that retransmissions provoked in our WLA. For this reason, we measured the average transmission rate in our experiments, that is 24 Mbps approximately. The per bit energy on g operating at 24 Mbps rate is 20.4 njoule for transmission and 6.4 njoule for reeption. Consequently the perentage of energy saved omparing the AP measurement based model with the stati weighted and our DFS model is derived by aounting both energy saved on the transmitter and on the reeiver side of the ommuniation. As depited in Fig. 3.b the stati weighted model onsumed 31.6% less power than the AP measurement based model and our DFS model ahieved 57% less power onsumption ompared again to the AP measurement based model. Therefore, we show the signifiant power savings that we ahieve by using our proposed sheme (7) in omparison with two other onsidered shemes (8), (9). VII. COCLUSIO AD FUTURE WORK In this work we presented a green DFS model for infrastruture WLA, whih presents a notieable energy effiieny ompared to a stati weighted model and an AP measurements deision model. As many manufaturers have not inluded in their APs funtionality the smart hoie of operating hannel, we tested our adaptive model in a stati environment regarding the ability of swithing to better operating frequenies. In our future work, we aim to investigate the stability of our model, when a WLA that uses our DFS model, operates among other WLAs that use the same model on hoosing their operating hannel. In order to explore how this stability an be ahieved, we are going to formulate our model using a game theoreti model and investigate if equilibrium exists. REFERECES [3] J-C. Chen, K. Sivalingam and P. Agrawal, Performane omparison of battery power onsumption in wireless multiple aess protools, IEEE IFOCOM 1998, San Franiso, CA, USA [4] J-H. Chang and L. Tassiulas, Energy Conserving Routing in Wireless Ad-ho etworks, IEEE IFOCOM 2000, Tel Aviv, Israel [5] IEEE Standard , Wireless LA Medium Aess Control (MAC) and Physial Layer (PHY) Speifiations ov [6] J-M. Choi, Y-B. Ko and J-H. Kim, Enhaned Power Saving Sheme for IEEE DCF Based Wireless etworks, Springer, Personal Wireless Communiations, vol. 2775/2003, Sep, 2003 [7] M-A. Malik and D. Shin, Collision Free and Energy Effiient MAC protool for Wireless etworks, IJCSS, vol. 7 o.9, Sep [8] J. Zhao, Z. Guo and W. Zhu, Power Effiieny in IEEE a WLA with Cross-Layer Adaptation, in Pro. IEEE ICC, Anhorage, Alaska, May 2003, pp [9] D. Qiao, S. Choi, A. Soomro and K. Shin, Energy Effiient PCF operation of IEEE a WLAs via transmit power ontrol, Comput. etw. 42, 1 May. 2003, pp [10] L. Guo, X. Ding, H. Wang, Q. Li, S. Chen and X. Zhang, Exploiting Idle Communiation Power to Improve Wireless etwork Performane and Energy Effiieny, in Pro. of IEEE IFOCOM Barelona, Spain, April 2006 [11] G. Athanasiou, I. Broustis, T. Korakis and L. Tassiulas, Routing- Aware Channel Seletion in Multi-Radio Mesh etworks, International Conferene on Communiations (ICC 2009) [12] B-J. Ko, V. Misra, J. Padhye and D. Rubenstein, Distributed Channel Assignment in Multi-Radio Mesh etworks, WCC 2007, Hong Kong Marh, 2007 [13] A. Raniwala, K. Gopalan and T. Chiueh, Centralized Channel Assignment and Routing Algorithms for Multi-Channel Wireless Mesh etworks, ACM Mobile Computing and Communiations Review 2004, vol. 8, pp [14] R. Akl and A. Arepally, Dynami Channel Assignment in IEEE networks, in Pro. IEEE Portable 2007: International Conferene on Portable Information Devies, Orlando USA, Marh 2007 [15] etwork Implementation Testbed Laboratory, [16] etwork Implementation Testbed for using Open Soure platforms, [17] OMF, Ontrol & Management Framework, [18] CERTH, The Centre for Researh & Tehnology Hellas, erth.gr/ [19] MadWifi open soure driver, [20] Iperf, [21] Atheros, [1] IEEE standard h supplement, Wireless LA Medium Aess Control (MAC) and Physial Layer (PHY) Speifiations. Spetrum and Transmit Power Management Extensions in the 5GHz band in Europe, 2003 [2] Y. Xu, J. Lui and D-M. Chiu, Improving energy effiieny via probabilisti rate ombination in multi-rate wireless networks, Elsevier, 2009