An Outband Paging Protocol for Energy-Efficient Mobile Communications

Transcription

1 246 IEEE TRANSACTIONS ON BROADCASTING, VOL. 48, NO. 3, SEPTEMBER 2002 An Outband Paging Protocol for Energy-Efficient Mobile Communications Apostolis K. Salkintzis, Member, IEEE and Chistodoulos Chamzas, Senior Member, IEEE Abstract In this paper a new protocol is proposed for reducing the power consumption of the battery-powered terminals in a mobile computing environment. We exploit the fact that, in a mobile data network mobile terminals do not continuously receive data and therefore they need not continuously operate their receivers. Nevertheless, they need to periodically check their traffic condition, that is, whether there are pending data for them or not. The proposed energy-efficient protocol is based on a paging procedure wherein a dedicated channel is used to alert (page) the terminals with pending traffic. Each terminal may check its traffic condition whenever it decides to by monitoring the paging channel. The protocol is evaluated through an approximated theoretical model and through computer simulation. We focus on deriving approximate formulas for the mean message delay, the message delay variance and the power consumption. It is shown that the proposed protocol can achieve considerable power saving at a cost of increased message delivery delay. Index Terms Energy-conserving protocol, energy consumption, energy saving, mobile data networks, power saving, protocol analysis, wireless communications. I. INTRODUCTION THE DEVELOPMENT of mobile data technology has exposed new opportunities to mobile computing. The emerging new services combined with the ramping up network performance and with the new wireless data transmission standards are quickly establishing an advanced framework, ready to serve the increasing mobility demand [1]. However, as mobile computing moves forward, mobile users are becoming increasingly demanding; they need service everywhere, at anytime. Therefore, the limited power resources of battery-operated mobile terminals is progressively becoming an annoying problem and network operators are forced to employ some kind of energy-efficient protocol as a means of extending the battery life of mobile terminals. In order to reduce battery-consumption, many mobile data networks and wireless LANs, such as MOBITEX [2], ARDIS [3], CDPD [4], IEEE [5] and HIPERLAN [6] apply some power-efficient protocols. Some details of these protocols can also be found in [7], [8]. The common idea behind all these protocols is the intermittent operation of receivers, which means Manuscript received May 13, 2002; revised August 7, This work was supported in part by the General Secretariat of Research and Technology, Greece, under the Project PENED 407. A. K. Salkintzis is with Motorola, GR-15125, Athens, Greece ( a.k.salkintzis@ieee.org). C. Chamzas is with the Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece ( chamzas@ee.duth.gr). Publisher Item Identifier /TBC that the mobile stations conserve power by operating discontinuously their receive units. The discontinuous reception can be proved very efficient in terms of power saving because as Stemm et al. showed for typical usage scenarios, by far the most power (about 90 percent) is drawn by listening to the radio channel [9]. Packet transmission and reception contributes only a few percent to the energy balance. Obviously, in a packet data network, intermittent reception raises considerable problems since mobile stations are not always capable to receive data. The usual approach to cope with these problems is by managing the wake-up/sleep scheduling of the mobile stations, that is, by controlling the wake-up periods wherein the mobile stations should be awake. In such cases, all mobile stations are synchronized and wake up at the same time intervals and, for this reason, the power-saving protocols that implement such wake-up synchronization are called synchronous power-saving protocols. In principal, all the powersaving protocols used today in mobile computing environments feature such synchronization attributes. However, there are various problems associated with the synchronous power-saving protocols. In case of MOBITEX, for example, mobile stations are forced to wake-up at every wake-up period and this may not be the most appropriate scheme for the users [7]. This is because users with low traffic (or no traffic at all) are forced to wake-up frequently if there is buffered traffic for other users. Hence, the power consumption of one mobile station depends on the activity of the other mobile stations, therefore, an efficient power management is not possible. On the other hand, in case of CDPD and IEEE , receivers are not forced to wake-up at every wake-up period but, rather, they may choose to remain asleep during some wake-up periods if the battery resources are reduced. In this case, a new problem arises from the fact that the base station does not explicitly know when a mobile station is ready to receive data (i.e., it is awake). To overcome this problem, stations that get ready to receive data, transmit a special link-control frame (called here Receiver-Ready Notification, RRN) to notify the network of their reception capability. However, such transmissions may have quite detrimental effects on power-saving characteristics, in particular, when the synchronous wake-up process is considered: Since receivers tend to wake-up at the same time, they also tend to transmit their RRN messages at the same time. These RRN transmissions compete simultaneously for uplink resources and have high probability to collide with each other. Therefore, retransmission of RRNs is likely to happen and extra power may be unnecessarily consumed. To overcome the problems associated with the synchronous power-saving protocols, other alternatives have been proposed, /02$ IEEE

2 SALKINTZIS AND CHAMZAS: AN OUTBAND PAGING PROTOCOL FOR ENERGY-EFFICIENT MOBILE COMMUNICATIONS 247 usually referred to as asynchronous power-saving protocols [13]. For example, a pseudo-random class of energy-conserving protocols is proposed in [10], [11], where the terminals wake-up pseudo-randomly and thus asynchronously to each other. The main advantage of this approach is that the base station can predict when every terminal will wake-up and therefore there is no need for RRN transmissions. In [12], [13] another protocol is proposed, namely, the in-band energy saving protocol, where the terminals wake-up completely randomly. In this scheme, the downlink resources are statistically multiplexed to transmit page and data messages. The base station continuously pages the terminals having buffered traffic until it receives one or more RRN messages. In this case, data transmission takes place and subsequently the paging process is resumed provided there is still buffered traffic. The theoretical treatment of this energy-saving protocol can be found in [14]. Further information about additional means that have been proposed in the technical literature for reducing the power consumption in wireless communications, can be found in [15] [18]. This paper proposes and studies another asynchronous power-saving protocol, namely, the outband protocol, which has been introduced in [19]. This protocol is based on the fundamental principles of the in-band energy saving protocol, however, it realizes the paging process by completely different means. In Section II, the protocol details are presented along with some assumptions that simplify the protocol modeling. In Section III, the protocol is approximately studied with the aid of a cascade queuing model, while, in Section IV, the performance of the protocol is evaluated under various service disciplines. In this context, we focus on the mean delay of message delivery and on the message delay variance. Additionally, we demonstrate the power-saving characteristics of the protocol. Finally, in Section V, we conclude with some notable implementation notes and we describe the major applications where this protocol can be applied. II. PROTOCOL DESCRIPTION In our mobile computing environment a number of battery-operated terminals, connected to suitable radio modems, communicate with a single base station using the outband power-saving protocol, therefore, their receivers are not always in operation. The protocol itself may be implemented either in the radio modems firmware or in the communication drivers of the terminal unit. Whatever the case, the radio modem should be capable of powering on and off the radio receiver and of supporting the appropriate power management functions. The downlink channel (from base to terminals) is further divided into two distinct channels: the paging and the data channel. The traffic for terminals with unknown reception state is buffered in the base station and the paging channel is used to continuously broadcast the addresses of these terminals. Every terminal may check its traffic condition (whether it has buffered data or not) by powering on its receiver and getting a page message. Should this page message identify that buffered traffic for this terminal exist, the terminal transits onto the data channel and sends a Receiver-Ready Notification (RRN) Fig. 1. The queuing model for the outband protocol. message to notify the base station that it awaits for its buffered data. As soon as it receives its pending traffic, the terminal switches back to sleep mode and the whole process starts over again. It is important note that, in contrast to the synchronous power-saving protocols, every terminal may check its traffic condition whenever it wants. In general, the outband protocol allows the utilization of varying-length page messages, e.g., depending on the number of terminals with pending downlink traffic. However, if a fixed-length encoding scheme is implemented, 1 then it is possible to apply a slotted configuration in the paging channel, where each page message is transmitted within a slot period. Such configuration will be beneficial from a power-saving point of view, because terminals may arrange to wake-up only during a slot duration and no power-up time will be wasted. This is accomplished at an expense of firmware complexity, by making the sleep period of the terminals a multiple of the slot duration. In the following, we adopt this slotted configuration for the paging channel. The configuration of the uplink channel (from the mobile terminals to the base station) and mainly the multiple access scheme, may affect rigidly the characteristics of the protocol, since RRN transmissions are carried on this channel. In a general case, a terminal may need to send more than one RRNs to successfully declare its reception availability, since wireless channel impairments as well as collisions may corrupt RRNs. However, as explained before, the asynchronous wake-up scheduling provides a robust mechanism against RRN collisions that results in reduced power consumption and reduced average message delay. Other advantages of the outband protocol, as compared to the synchronous power-saving schemes, include the easy adaptation of power consumption to the current battery conditions and the lack of wake-up synchronization overhead. 1 A fixed-length bitmap encoding is practically possible. If a single page message cannot encode all the necessary terminals, then successive page messages may be used.

3 248 IEEE TRANSACTIONS ON BROADCASTING, VOL. 48, NO. 3, SEPTEMBER 2002 Fig. 2. Message arrival/departure timing in the paging queue. III. PROTOCOL MODELING AND ANALYSIS The model for the analysis of the outband energy-efficient protocol is based on the relatively simple cascade queuing system illustrated in Fig. 1. The base station maintains two queues, a paging queue and a service queue. Every data message that arrives to the base station enters into the paging queue, where it remains until the mobile terminal that the message is addressed to sends a RRN. Hence, the paging queue keeps all the messages that are addressed to mobile terminals, which are not in receive mode yet. After a mobile terminal responds to a page and sends a RRN, all its buffered messages are transferred from the paging queue into the service queue, where they wait to be transmitted on the data channel. The service discipline module at the bottom of the service queue (see Fig. 1) represents a function that selects messages for transmission with a particular discipline. System performance under various service disciplines is evaluated in Section IV. We are mainly interested in finding approximate formulas for the average length of the paging and service queues, as well as for the average message delivery delay. Below we summarize the assumptions used in our theoretical analysis: 1) The system consists of statistically identical mobile users serviced by one base station. These users are free to monitor the paging channel whenever they want to check if there is buffered traffic for them. 2) The sequence of message arrivals is assumed to be a Poisson process with total mean rate, therefore, the average traffic per user is. 3) The transmission time of a data message is exponentially distributed with an average value 1/. 4) For the purposes of our theoretical analysis, we assume that every RRN encounters no transmission delays and no corruption. This assumption will yield the best-case performance of the protocol and it will make our study independent of the peculiarities of the uplink channel. 5) Mobile terminals select a slot to wake-up at random, i.e., in each slot a terminal wakes-up with probability, which is constant and the same for all mobile terminals. This random scheduling have also been considered in other similar works, e.g., [10] [14]. 6) The paging channel is considered slotted with a slot duration. During a paging slot the base station transmits a page message unless there is no buffered traffic. 7) The traffic per mobile terminal,, is considered small. Otherwise, there is no point to implement discontinuous reception. 8) The base station has large buffer capabilities and we may neglect the probability of a queue overflow. A. Message Delay Queue Length We now proceed by finding the average length of the queues maintained by the base station and the average time that a message remains in these queues. These values will help a system designer to estimate the required buffer capacity of the base station and the total average delay that a message experiences in the downlink channel. 1) The Paging Queue: As already mentioned, every message that arrives at the base station enters into the paging queue where it remains until the base station receives a RRN from the mobile terminal that the message is addressed to. Fig. 2 shows a typical time diagram for this queue. In this figure, arrows over the time axis represent messages arriving to the queue and arrows below the time axis represent messages departing from the queue. As we can see, message M1 arrives during slot 2 and immediately enters into the paging queue. So, starting from slot 3, the base station also pages the mobile terminal, say T1, that this message is addressed to. According to Fig. 2, message M1 leaves the paging queue at the end of slot 4, which implies that the base station has received a RRN from terminal T1 at the end of this slot. As also indicated in Fig. 2, at the end of a paging slot many messages may leave the paging queue since many RRNs may arrive simultaneously (e.g., see the departures of messages M2, M3). Let denote the time a data message remains in the paging queue. Note that, will be zero if the message is addressed to a mobile terminal that has already sent a RRN and it is already in receive mode. However, when the traffic per user is small (as assumed) the probability to be zero is very small and we can assume that every arriving message always faces a delay in the paging queue. Under these conditions, the paging delay can always be written as: where is the interval from the message arrival till the beginning of the next paging slot and is the number of pages transmitted before the mobile terminal sends a RRN. Since all mobile terminals perform the same random wake-up scheduling (assumption 5), has a geometrical distribution with average value 1/ and the average time a message remains in the paging queue,, is: (1) (2)

4 SALKINTZIS AND CHAMZAS: AN OUTBAND PAGING PROTOCOL FOR ENERGY-EFFICIENT MOBILE COMMUNICATIONS 249 where represents the average value. As proved in Appendix, the probability to find data messages in the paging queue under steady-state conditions is a simple Poisson distribution with parameter (15), thus, the expected number of messages in the paging queue under equilibrium is (3) Since is known, it is straightforward to evaluate the number of data messages that leave the paging queue at the end of an arbitrary slot: messages leave at the end of a slot (4) 2) The Service Queue: As indicated by Fig. 1, messages that exit from the paging queue immediately enter into the service queue, where they wait to be transmitted on the data channel. Since messages exit from the paging queue only at slot edges and since a group of messages (i.e., a bulk) may exit simultaneously, we deduce that the service queue receives bulk message arrivals at discrete time instants. This input process differs from the usual case where a queue receives single messages at any time instant (like the notorious continuous-time M/M/1 queue [20]). In the Appendix, we derive the approximate expressions for both the average number of data messages in the service queue and the variance of this queue. For the specific case of exponentially distributed message lengths, we have: Note that, as compared to the continuous-time M/M/1 queue, the service queue in our case exhibits larger average length, as long as the page transmission time,, is greater than zero. When, the same result as with the M/M/1 queue is derived. In Fig. 3 we plot the variance of the service queue length for three values of slot duration. The case where corresponds to a system where the receivers are always in operation and, consequently, no paging is performed (this system is modeled as a continuous-time M/M/1 queue). We can observe that, the variance of the service queue length is considerably increased compared to the continuous-time M/M/1 case. In fact, the larger the slot duration, the larger the variance. This means that, in practice, we must make the capacity of the system queue larger than usual if we want to keep the same message drop (or queue overflow) probability. Finally, using (5) and Little s result [20], [22] we calculate the total average message delay in the downlink channel,, and the total average length of the paging and service queue as (5) (6) Fig. 3. s. The variance of the service queue length for three values of slot duration B. Energy Consumption The energy consumed 2 by a mobile terminal in any sufficiently large time interval of duration, can be easily decomposed into three parts: The energy consumed due to sporadic checking of its traffic condition, the energy consumed due to data reception (i.e., when a RRN has been sent and the receiver remains in operation to accept the forthcoming data), and the energy consumed due to the transmission of RRNs. If, in the time period, data messages arrive for a particular terminal, then (assuming again that is small) the terminal will send RRNs and will transit times to receive mode in that interval. Therefore, the terminal will be in receive mode for an average duration and the rest of the time,, will perform power-up/power-down oscillations. Since the average value of is, where is the mean message arrival rate per terminal, the average energy consumption in interval will be where is the power consumption during receiver operation and is the energy consumed by an RRN transmission. Denoting the transmission-to-reception power ratio by and the RRN transmission duration by (thus, ), the average power consumption of the terminal can be written as The ratio of the average power consumed (in order to sustain communication on the downlink channel) by a mobile terminal implementing the outband energy-efficient protocol, to the same 2 We refer to the energy consumed by a mobile terminal in order to receive messages. (7) (8) (9)

5 250 IEEE TRANSACTIONS ON BROADCASTING, VOL. 48, NO. 3, SEPTEMBER 2002 As can be identified from Fig. 4, the optimum data channel capacity depends linearly on the total downlink message rate. Therefore, unless the data channel capacity is dynamically adapted to the total downlink traffic rate, the system can not work continuously at the optimum point. This is another price we have to pay for conserving energy. Fig. 4. Message delay versus data channel capacity for various (D; p) pairs. Mean message length is 200 bits and total message arrival rate is 4 messages per second. power consumed by a terminal that continuously operates its receiver, is defined as the normalized downlink power consumption (NDPC). From (9) the NDPC is expressed as: (10) It is important to note that (10) is valid only when the traffic per user is small, as we have assumed. C. Downlink Partitioning As already mentioned, the proposed outband protocol devotes a portion of the available downlink capacity to the paging process. A problem that naturally arises from this dedicated assignment is how to make the overall downlink partitioning. Let s denote by the capacity (measured in bits/sec) of the paging channel and by the capacity of the data channel. Note that is constant. We need to find the proper, pair that minimizes the total downlink message delay given by (6). We can express as a function of by substituting to (6) the following values for the paging slot duration and the maximum message transmission rate : (11) where (bits) is the length of a page message and 1/ (bits) is the average length of a data message. In Fig. 4 we plot versus the data channel capacity for a typical system with kb/s overall downlink capacity. The mean message length is 200 bits and the total message arrival rate is 4 messages per second. The various curves shown in this Fig. 4 correspond to various ( ) pairs. Observe that, for every pair there is a single data channel capacity that minimized the average message delay. It is also interesting to see, that the lowest curve, corresponding to and, exhibits a wide flat range where the delay is almost equal to minimum. This shows that, as and (i.e., we approach the continuous-reception case), the average message delay gets less sensitive on capacity partitioning. IV. PERFORMANCE EVALUATION In this section we present the performance of the outband energy-efficient protocol by means of the theoretical results derived in the previous section and the results of computer simulation. 3 We mainly consider the average message delay (in the downlink direction), the message delay variance and the power consumption characteristics of the protocol. Additionally, we display the expected number of messages queued at the base station, since this is an important parameter that affects the storage allocation at the base station. In Fig. 5 we plot the expected number of messages queued at the base station versus the total normalized downlink traffic intensity. Note that corresponds to an average arrival rate equal to the maximum rate that messages may be transmitted in the overall downlink channel. Curves 1 3 correspond to the outband energy-efficient protocol, each one for a different value of the data channel capacity. The parameter shown in the diagram represents the length of a page relatively to the average message length. Both theoretical [derived from (7)] and simulation results are displayed and it is interesting to see that they are almost identical. This justifies that our analysis gives satisfactory results as far as queued messages are concerned. As we can observe from Fig. 5, when the total downlink traffic is expected to be small, it is better to allocate a small data channel capacity in order to reduce the number of queued messages and the message delay. However, as downlink traffic increases, it is better to increase the capacity of the data channel in order to accommodate the increased traffic demand. In Fig. 5 we also plot the expected queued messages when no paging takes place and when all receivers continuously operate (curve 4). It is easy to observe that, for conserving power at the mobile terminals, the base station needs to maintain greater buffer resources than usually. We now consider the system performance under three service disciplines, namely, First Come First Served (FCFS), exhaustive service, and nonpreemptive priority service. 1) FCFS Service Discipline: In FCFS service discipline, the first message coming into the service queue is the first one to be served. To resolve the ambiguity caused by the bulk arrivals (regarding which message comes first), we assume that whenever a bulk contains more than one message, these messages are placed randomly at the tail of the service queue. Generally, when a FCFS discipline is implemented a mobile terminal receives one data message at a time despite the fact that there may be more messages for it in the service queue. 4 3 For this simulation, we wrote a specific C program, which was generating Poisson traffic, was buffering the traffic and was forwarding the traffic to the data channel only after the recipient responded to paging. 4 A mobile terminal may go to the sleep mode only after it has no more messages in the service queue. For this purpose, every received message indicates if there are more pending messages in the base station or not.

6 SALKINTZIS AND CHAMZAS: AN OUTBAND PAGING PROTOCOL FOR ENERGY-EFFICIENT MOBILE COMMUNICATIONS 251 Fig. 5. Number of messages queued at the base station versus total normalized traffic intensity. Solid curves represent theoretical results (7), while dashed curves represent simulation results. Fig. 6. Average message delay versus normalized downlink traffic demand in case where a = 0:1. This policy causes mobile terminals to remain for long periods in receive mode but also assures that communication resources are fairly shared between users, i.e., users with high downlink traffic do not monopolize the data channel. In Fig. 6 we demonstrate the expected message delay versus the normalized downlink traffic intensity for three values of data channel capacity. It is noted that the expected message delay is considered normalized with respect to the mean message transmission time. For each case, both theoretical (solid lines) and simulation (dashed lines) results are plotted. Again, the expected message delay of the common continuous-reception case is included for comparison. The difference between simulation and theoretical curves comes from the assumption that every arriving data message stays in the paging queue. However, since Fig. 7. Average message delay versus normalized downlink traffic demand in case where a =0:5. this is primarily true when the traffic is small, we note that the difference between theoretical and simulation curves increases as increases. In Fig. 7 we plot again the expected message delay but for larger page messages. In fact, the length of a page message has been increased by 5. An interesting observation is that, when is large, message delay tends to remain relative constant over the entire usable traffic range. This is expected because, when is large, the dominant delay is introduced by the paging process, which is independent of the downlink traffic. Moreover, we note that as the length of page messages is reduced, the curves tend to join at low traffic conditions. Indeed, in Fig. 6, for small values of, the message delay is increased by 45% when increases from 0.4 to 0.8, whereas, in Fig. 7, the message delay is

7 252 IEEE TRANSACTIONS ON BROADCASTING, VOL. 48, NO. 3, SEPTEMBER 2002 Fig. 8. Average message delay variance for different values of data channel capacity. increased by 130% when goes again from 0.4 to 0.8. This indicates that, if we can make the length of pages small, then we can choose a large data channel capacity without major performance degradation at low traffic conditions. Fig. 8 illustrates the message delay variance derived from simulation versus the normalized downlink traffic intensity. The variance of the message delay develops considerable increase when compared to the continuous-reception case and this is caused by the extra randomness, which is introduced by the paging process. At low traffic rates, the variance is increased by 7 times, relative to the continuous-reception, when the data channel is 0.4, and by 25 times when the data channel is 0.8. In other words, a 100% increment of the data channel capacity causes a 257% increment of the variance. Consequently, if we slow down the paging process the variance of the message delay grows up rapidly. Fig. 9 focuses on the normalized downlink power consumption (NDPC), defined in Section III. The curves show the NDPC versus normalized downlink traffic demand for a network with 50 users and for a network with 100 users. In our simulation and theoretical models, for a constant downlink traffic, the traffic per user reduces as the population increases, hence the consumption for appears to be smaller than for. The solid lines represent the theoretical results derived from (10), which, once more, are more pessimistic than simulation results for the same reason explained earlier. We note that the NDPC increases almost linearly with the downlink traffic demand up to a point where the channel starts to saturate. In this case, the curves quickly converge to 1 because every terminal is forced to continuously operate in receive mode in order to accept its large buffered traffic. However, it is apparent that the protocol exhibits considerable power-saving features mainly where the traffic per user is small. An extremely important parameter concerning power consumption is the transmit to receive power ratio. This parameter, together with (the duration of RRNs), must be kept as small as possible in order to limit the power consumption caused Fig. 9. Normalized downlink power consumption versus total downlink traffic for a system with 50 users and a system with 100 users. by the transmission of RRNs. Otherwise, the power-saving characteristics of the protocol may become negative. However, our simulation results have shown that the NDPC remains smaller than 1 under all common values of, which range from 5 to 60 [13]. 5 2) Exhaustive Service Discipline: In exhaustive service discipline, all pending messages in the service queue addressed to the same terminal are grouped and transmitted together. In this way, a terminal receives all its buffered traffic in a short burst and, thus, the average time the terminal remains in receive mode is reduced. Consequently, the average power consumption may be expected to reduce and this is our main motivation toward the exhaustive service discipline. However, as we explain below, this is not always true. In Fig. 10 we plot the percentage of time that a terminal remains in receive mode in order to accept its buffered traffic versus the overall normalized downlink traffic. For example, when, a terminal spends approximately 12% of its time in receive mode. The solid line corresponds to FCFS discipline while the dashed line corresponds to exhaustive discipline. As we may observe, in the case of exhaustive service, the average time a station remains in receive mode is indeed reduced, thus, an extra power-saving gain can be obtained. Nevertheless, in the case of exhaustive service, the average number of RRNs per time unit (see Fig. 10) is also increased 6 and extra power is consumed by the additional transmissions. Therefore, the power-saving gain achieved by the reduced time in receive mode may be counterbalanced by the extra power cost of RRN transmissions. In fact, if the transmit to receive power ratio is large, the exhaustive service may exhibit increased power consumption. On the other hand, when is small, the power con- 5 Even when g is very large, a real time implementation could estimate the NDPC value and switch to continuous reception mode when this value is found larger than 1. 6 The main reason for this, is that the probability an arriving message for terminal T1 to find other messages in the service queue also for terminal T1 is reduced.

8 SALKINTZIS AND CHAMZAS: AN OUTBAND PAGING PROTOCOL FOR ENERGY-EFFICIENT MOBILE COMMUNICATIONS 253 Fig. 10. Number of RRNs per time unit and percentage of time that a terminal remains in receive mode versus downlink traffic. The plot compares exhaustive and FCFS disciplines. sumption is slightly reduced. Therefore, we conclude that the exhaustive service is beneficial in cases where the transmit-toreceive power ratio is small, e.g., in wireless LANs. We note that an exhaustive service discipline is always accompanied by a slight increase in message delay variance. 3) Non-Preemptive Priority Discipline: Now consider the case where every mobile terminal is assigned a unique priorityclass ( ) number. The terminal with the smallest pc number has the highest service priority, that is, messages for it are transmitted before the other messages in the service queue. In practice, this priority assignment is useful and easily implemented. For example, the base station may assign a priorityclass number to every new terminal that registers with it based on a battery-condition indication. In this way, terminals with low battery indication may be assigned a small number (in order to operate with reduced power consumption), while terminals with high battery indication may be assigned a higher number. In Fig. 11 we demonstrate how the priority scheme affects the average message delay in the outband energy-efficient protocol. The graph corresponds to a system with 50 users, each one operating with a wake-up probability. The data channel capacity is equal to 0.4. The cautious reader will observe that although some curves exceed the maximum traffic point (i.e., ), they are unrealistic beyond that point because the system overflows. As we can see, about the half of the users experience larger message delay when compared with the FCFS case. The message delay of the highest priority user (i.e., with ) exhibits a completely flat response, while the message delay of the lowest priority user presents a sharp ramp up. Similar observations can be made for the normalized downlink power consumption that is presented in Fig. 12. In this priority situation, high priority users remain for short periods in receive mode but, in general, they are forced to transmit RRNs Fig. 11. Average message delay for a system with 50 prioritized users. The FCFS curve represents the average message delay when no priority is applied. more frequently. On the other hand, low priority users transmit less RRNs but remain for longer period in receive mode. According to Fig. 12, most users, even the ones with low priority, experience reduced power consumption as compared to FCFS. This is caused by the radical reduction of RRN transmissions. V. CONCLUSION We have shown that the proposed outband protocol exhibits power-saving characteristics at a cost of increased mean message delay and message delay variance. The attainable power-

9 254 IEEE TRANSACTIONS ON BROADCASTING, VOL. 48, NO. 3, SEPTEMBER 2002 independent power management facilities, which are of considerable importance in a mobile computing environment. With this protocol, every mobile terminal may retain a dynamically tunable wake-up sleep cycle, proportional to its current battery status and apply a distinct network-independent algorithm to manage its own power resources. APPENDIX In this Appendix, we present the theoretical analysis of the queuing model shown in Fig. 1. The queues shown in the model are studied separately; first we study the paging queue and then the service queue. This separation is possible because of the assumption that the traffic per user is small. Fig. 12. Normalized downlink power consumption for a system with 50 prioritized users. The FCFS curve represents the normalized downlink consumption when no priority is applied. saving depends on the wake-up sleep scheduling, on the average downlink traffic per user, on the page message length and on the capacity of the data channel. In general, when the traffic per user is small, 90% power saving can be exhibited, while the expected message delay is increased by 4. It is clear that, for a number of delay-tolerant applications (e.g., transfer), the protocol may provide an ideal energy-efficient solution, because it allows individual terminals to implement a network-independent power management. The most profound benefits of the protocol are established under low traffic conditions, where the mean traffic per user is small. At these traffic rates both the mean message delay and the message delay variance exhibit low degradation and considerable power saving can be achieved. Therefore, patch-type applications like two-way messaging, small file transfer and exchange, are likely the most suitable application to be supported. Since a low transmit-to-receive power ratio is desired for mitigating the effects of RRN transmissions to the power consumption characteristics, networks employing pico and microcellular arrangements like digital cordless systems and wireless LANs are considered as the most favorable networks for implementation, since is really small in such networks. There are also other reasons that render these systems suitable for the outband energy-efficient protocol. For example, they feature extremely small round trip delay, thus, they provide for a fast returning channel, which is critical to the RRN transmissions. Additionally, the negligible corruption probability assumed for the RRNs is realized more easily in these networks, because they usually operate on high capacity channels with small bit error rate. Along with further enhancements the proposed protocol can be envisaged as an optional power-saving feature, where terminals that run out of energy switch to power saving mode after notifying the base station. In contrast to the synchronous powersaving protocols, the proposed protocol provides the means for A. Paging Queue Assuming we start with an empty paging subsystem at slot 1 (Fig. 2), we find, the probability to have buffered data messages in the paging queue right after the slot,. If a data message arrives during slot,, and is uniformly distributed in the interval [1, ], the probability that this message will have been served by the end of slot is service will have end by service will have end by arrival occurs during slot (12) where, denotes the time that the data message remains in the paging queue. The probability can be found if we condition on the number of arrivals in the interval (0, ) and then we drop the condition: where messages after messages arrive in Since we have assumed Poisson arrivals: (13) (14)

10 SALKINTZIS AND CHAMZAS: AN OUTBAND PAGING PROTOCOL FOR ENERGY-EFFICIENT MOBILE COMMUNICATIONS 255 Fig. 13. Service queue timing. For the equilibrium distribution end up to and from (14) we (15) B. Service Queue We find now the average number of messages in the service queue, as well as the variance of the number of messages in that queue. We note that the service queue is similar to the usual continuous-time M/M/1 queue, except that arrivals occur only at discrete time instants and every arrival may be composed of many messages. We refer to the typical timing diagram shown in Fig. 13. Again, arrows over the time axis represent messages coming into the service queue and arrows below the time axis represent messages going out of the service queue. With we represent the th data message that leaves the service queue and with we represent the service period of the data message. Let be the number of messages left in the queue just after the nth message departure (see Fig. 13). The sequence is the number of messages in the service queue at selected time instants and it forms an imbedded Markov chain. Solving for the probability generating function of when [denoted as ] in a similar way as in [21, pp. 181], we find: duration. However, an interval includes either or arrival points (slot edges), where denotes the integer part of the real number. Also the probability of the event includes arrival points is, since the beginning of the service time is uniformly distributed in a slot interval. So, we can write and from (17), (18), where and is the probability generating function of (4), (18) (19) (20) We can evaluate (19) by cutting the integral into intervals of size : (16) where and is a random variable representing the number of messages that arrive during a service period. may be found as follows: (21) Equation (21) is valid for every and it can be used to find a solution for any message length distribution. For exponentially distributed lengths where, we find arrivals occur during a service interval (22) or (17) where is the pdf of the service time and is the probability messages to arrive during a service period with Equation (22) gives the probability generating function of the number of data messages that arrive during a message service period. It is significant to observe that, when then, which is the result for the typical M/M/1 queue. The expected number of arrivals during a service interval is obtained by taking the first derivative of (22) at the limit : (23)

11 256 IEEE TRANSACTIONS ON BROADCASTING, VOL. 48, NO. 3, SEPTEMBER 2002 Using (16), (22) and (23) we calculate the average number of data messages in the service queue: [22] H. Kobayashi and A. G. Konheim, Queueing models for computer communications system analysis, IEEE Trans. Commun., vol. COM-25, pp. 2 28, (24) Finally, the variance of the queue length,, can be calculate from the following equation (25) where and represent the first and the second derivatives of. REFERENCES [1] J. E. Padgett, C. G. Guenther, and T. Hattori, Overview of wireless personal communications, IEEE Commun. Mag., vol. 33, no. 1, pp , Jan [2] Mobitex Interface Specification, RAM Mobile Data, 10 Woodbridge Center Drive, Woodbridge, NJ , [3] K. Pahlaval and A. H. Levesque, Wireless data communications, Proc. 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Salkintzis (M 98) received his Diploma in 1991 and his Ph.D. degree in 1997, both from the Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece. From 1992 to 1997 he was a Research Engineer at the Democritus University, studying mobile data networks and working on research projects dealing with the design and implementation of wireless data networks and protocols. In 1999 he was a Sessional Lecturer at the Department of Electrical and Computer Engineering, The University of British Columbia, Canada, and from October 1998 to December 1999 he was also Post Doctoral Fellow in the same department. During 1999 he was also a Visiting Fellow of Advanced Systems Institute of British Columbia, Canada, and during 2000 he was with the Institute of Space Applications and Remote Sensing (ISARS) of the National Observatory of Athens, Greece, where he conducted research on digital satellite communication systems. Since September 1999 he has been with Motorola Inc., working on the design and standardization of modern telecommunication networks, such as GPRS and UMTS. Dr. Salkintzis has served as principal guest editor in a number of special issues, including The Evolution of Mobile Data Networking for IEEE Personal Communications, Multimedia Communications over Satellites, for IEEE Personal Communications, IP Multimedia in Next Generation Mobile Networks: Services Protocols and Technologies, for IEEE Wireless Communications. He has served as referee for numerous IEEE journals and international conferences, including Globecom99, Globecom00, ICC2000, VTC99, VTC00, Globecom01, ICC01. He has organized several technical sessions in many of these conferences and has chaired most of them. His primary research activities lie in the area of wireless digital communication systems and networks, and particularly in mobile channel modeling, diversity techniques in multipath fading channels, error-correction coding, adaptive channel equalization, radio modem design with DSPs, and multiple access and data link protocols. Currently, he is most active in the design and standardization of GPRS and UMTS networks and he is an active participant and contributor in 3GPP standardization body. Dr. Salkintzis is a Member of the IEEE and a member of the Technical Chamber of Greece. Christodoulos Chamzas was born in Komotini, Greece. He received the Diploma degree in electrical and mechanical engineering from the National Technical University of Athens, Athens, Greece, in 1974 and the M.S. and Ph.D. degrees in electrical engineering in 1975 and 1979 from the Polytechnic Institute of New York, Farmingdale. From 1979 to 1982 Dr. Chamzas was an Assistant Professor with the Department of Electrical Engineering at Polytechnic Institute of New York. In September 1982 he joined AT&T Bell Laboratories, Holmdel, NJ, where he was a member of the Visual Communications Research Department until 1990, where he worked on adaptive systems, mobile communications, multimedia image databases and image coding. Since September 1990, he is a member of the Faculty of the Electrical and Computer Engineering Department, Democritus University of Thrace, where he is Director of the Electric Circuits Analysis Lab. of the Image Processing and Multimedia Unit, and Director of the Cultural and Educational Technologies Institute. He has been a major player in the definition, design, and implementation of the CCITT/ISO (JBIG, JPEG, etc.), standards for coding, storage, and retrieval of images (color and bilevel) an area where he holds six international patents. In , he was a visiting professor with the Department of Computer Science at the University of Crete, Iraklion, Greece. Since 1994, he is a member of the Telematics for Knowledge Working Party of EE. He has held summer positions in Greece, England, Portugal, as well as at Bell Laboratories. His primary interests are in digital signal processing, image coding, multimedia, and communications systems. He is currently interested in the implementation of multimedia image data base algorithms either with fast software or with VLSI design. Dr. Chamzas is a member of the Technical Chamber of Greece, Sigma Xi, and was an Editor in the IEEE TRANSACTIONS ON COMMUNICATIONS.