A Polling List Management Method Using Orthogonal

A Polling List Management Method Using Orthogonal Signalling in Clusters of Heterogeneous Networks Jae Hoon Ko, Soonmok Kwon and Cheeha Kim Department of Computer Science and Engineering Pohang University of Science and Technology (POSTECH) 790-784 San 31, Hyoja-Dong, Nam-Gu, Pohang, Gyungbuk, S.Korea {roengram, smok80, chkim}@postech.ac.kr

Abstract— Heterogeneous wireless networks are composed of nodes with different transmission range, energy capacity, or computation power. Such networks can achieve high performance and energy efficiency by employing clustering mechanism, where high-power nodes become cluster heads and others join nearby clusters. Due to difference in transmission range, intra-cluster transmission is asymmetric; the cluster head can directly transmit data to all of its member nodes, whereas the member nodes need to perform multihop transmission to reach the cluster head. Given that the network is relatively static, polling-based scheme is a suitable medium access method for intra-cluster transmission because of its high energy efficiency and QoS support. A major challenge of polling-based methods is polling list management, which is a method to determine which nodes need to be polled. Without such information, the cluster would poll many inactive nodes, resulting in significant waste of network resource. In this paper, an efficient polling list management scheme is proposed for intra-cluster communication in heterogeneous networks. The proposed scheme exploits orthogonal signalling to allow equidistant nodes to report their activeness simultaneously. The feasibility of orthogonal signalling is examined through simulations under a realistic channel model, and the performance of the proposed scheme is compared with two other existing algorithms by measuring the average time required to update the polling list and gather data packets from all the active nodes. The result shows that the proposed scheme performs best especially when active node ratio is not high.

I. I NTRODUCTION Heterogeneous networks consist of nodes with different capabilities in terms of transmission range, energy budget, or computation power. To benefit from such diversity, clustering mechanism is often employed; powerful nodes become cluster heads that form the backbone of the network, while ordinary nodes perform intra-cluster communication only [1][2]. Because cluster heads take the burden of relaying data over a long distance, ordinary nodes can save a significant amount of energy. In addition, cluster heads are capable of supporting complex data manipulation mechanisms that help to maximize network performance [3][4]. For intra-cluster communication, a polling-based method such as IEEE 802.11 PCF [5] is a viable medium access scheme because the cluster head can directly reach its member nodes at once; the reverse may not hold since ordi-

nary nodes have shorter transmission range or tighter energy budget [6]. Although polling-based medium access schemes are less robust compared to contention-based methods in a highly changeable network, they provide several advantages in a relatively static network. First, because all transmissions are governed by a cluster head, it is possible to schedule transmissions to guarantee some quality of service metrics such as delay, throughput, and fairness. Moreover, a cluster head may alleviate fading and inter-symbol interference by using a special adaptive array of antenna elements that can be directed towards the transmitting node [7]. Lastly, pollingbased schemes are more energy-efficient; in contention-based methods, several nodes may decide to send data simultaneously, resulting in collision; the RTS/CTS scheme employed to minimize collision is costly in that extra control packets should be exchanged for every data transmission; nodes should be awake to constantly listen to the radio because packets may arrive at any time and have to be decoded to find out their destinations [6]. In this paper, we focus on a polling-based intra-cluster transmission in a relatively static heterogeneous network. We assume that inter-cluster interference is avoided by using methods proposed in [6][8]. One major challenge of polling-based methods is polling list management, meaning that a cluster head should know which member nodes are active, i.e. having packets to send, before starting polling. Without such information, the cluster head may have to poll all nodes regardless of their actual status. This could cause significant decrease in channel utilization [9]. In this paper, we propose a novel polling list management method. By exploiting orthogonal signalling, the proposed method allows nodes that are equidistant to the cluster head (in terms of hop distance) report their activeness simultaneously. These reports are collected by one-hop closer nodes and aggregated with their own activeness reports. The aggregated reports are then transmitted to the next closer nodes in the same manner, until reaching the cluster head. This way, the cluster head can efficiently update the polling list. The remainder of the paper is organized as follows. In Section II previously suggested schemes are introduced. Section III briefly explains our previous work, on which the

proposed method builds. Section IV gives the detail of the proposed scheme. In Section V we evaluate the proposed scheme through simulations. Section VI concludes the paper.

Active STA detection phase

BS

B/Q

POLL

II. R ELATED W ORKS

Active STAA

TRA

Several methods have been suggested to solve the polling list management problem [7][10][11][12]. However, they concentrate on a single-hop network, where member nodes can reach their cluster heads directly, and vice versa. In this paper, we consider a cluster with asymmetric transmission where data from some member nodes should be relayed by others to reach the cluster head. Polling in multihop networks is studied in [13][14][8]. These works assume that all nodes including cluster heads have the same transmission range; hence, heterogeneity is not considered. [6] investigates a multihop polling method in clusters of heterogeneous sensor networks. This method, which will be referred to as twostep polling, first polls a carefully selected subset of nodes to gather activeness information. More specifically, while the data packets from the selected nodes are relayed to the cluster head, each relay node specifies the number of pending packets in the data packets. Upon receiving those data packets, the cluster head updates the polling list. In the second step, the cluster head calculates an energy-efficient polling schedule based on the polling list. Unlike the two-step polling method that relies on normal data signalling for polling list management, our proposed scheme exploits orthogonal signalling for better efficiency. A simulation that compares our proposed scheme with the two-step polling will be presented in Section V.

Active STAB

TRB

Inactive STAC

ACK DATA

NTRC

Fig. 1.

Frame transfer example of the OSPCF

false detection probability, respectively. Furthermore, we used the bit-wise inverse of a TR as its NTR. For example, if a TR is [-1 1 -1 1] then its NTR is [1 -1 1 -1]1 . By doing so the occurrence of false detection can be significantly reduced, as will become clear later in this section. Detection of a TR is performed as follows. Say that a TR of a station i is represented as an array of L symbols ui [k] and its NTR as vi [k] = P(−1) × ui [k], P1 ≤ k ≤ L. The received signal r[k] is then j∈A uj [k] + m∈I vm [k], where A is the set of active stations and I the set of inactive stations. The correlation Γi is then: Γi

L X

=

k=1 L X

=

u∗i [k]r[k] u∗i [k](

( =

X

uj [k] +

j∈A

k=1

III. P REVIOUS W ORK The polling method we propose in this paper is an extension of our previous work [15], which is a polling list management method for WLAN. Henceforth, the method will be referred to as the Orthogonal Signalling-based PCF (OSPCF) to distinguish it from the scheme proposed in this paper. The OSPCF presumes that every station is assigned with a pair of bit sequences called Transmission Request (TR) and Negative Transmission Request (NTR) when associated with a base station (BS). These bit sequences represent activeness and inactiveness respectively, and are unique to a station so that they can be used as its identity. The contention free period (CFP) of the OSPCF consists of two phases: active station detection phase and polling phase (Fig. 1). At the start of the first phase, the BS broadcasts a QUERY message that can be piggybacked on a BEACON message. Upon receiving this message, active stations respond with their TRs, whereas inactive stations transmit NTRs. Since the signals are sent simultaneously, the BS receives the combined signal. From the combined signal the BS detects transmitted TRs to identify active stations. In the polling phase, the BS polls the identified stations. To detect a specific TR from a combined signal, we used orthogonal codes as TRs. Orthogonal codes such as Walsh codes [16] are known to have high auto-correlation and low cross-correlation, which lead to high detectability and low

Polling phase

X

vm [k])

m∈I

PL ∗ k=1 ui [k]ui [k] PL ∗ −1 × k=1 ui [k]ui [k]

if i ∈ A if i ∈ I

PL , since k=1 u∗i [k]uj [k] is zero if i 6= j by the property of Walsh codes. Note that ∗ represents the complex conjugate, which can be omitted because symbols are all real values in this paper. The BS then determines that the TR is present if Γi is positive. If the NTR is transmitted instead, Γi is a large negative value, which is likely to remain negative even in a severely noisy channel. Therefore, making the bit-wise inverse of a TR as its NTR helps to reduce false detection. Fig. 2 shows an example of signal combination and detection process using 4-bit Walsh codes as TRs. TRA

1

TRB

1

TRC

1

NTRD

1

-1 -1

-1 -1

Combined 2 Signal

TRA 1

1

-1 -1

-1

TRB 1

-1

-1

1

4

1 Calculate Correlation

4

-1

TRC 1

-1

1

-1

4

-1 -1

TRD 1

1

1

1

-4

1

inverse -2

Fig. 2. 1 We

-1 -1

-2

-2

2

-2

-2

TR/NTR signal combination and detection

represent bit 0 as symbol -1 and bit 1 as 1 in this paper

-2

The OSPCF should address several practical issues: recognizing combined signals, detecting misaligned TR/NTRs, and signal strength equalization. By prepending a pseudorandom sequence to all TRs and NTRs, a combined signal can be correctly recognized. To detect misaligned TR/NTRs, the BS calculates a number of correlations by shifting the TR’s alignment with the combined signal by one symbol. Then the average correlation is compared with zero to determine presence of the TR. Lastly, signal strengths can be equalized by employing a closed-loop power control mechanism, where stations adjust their transmission powers according to feedback from the BS [16].

fading or noise. The signals are then combined and received by their parent node B. Node B then detects TR/NTR senders as outlined in Section III. In the next cycle, the cluster head broadcasts a QUERY message with level 2, to which node B responds with its TR combined with T RA and N T RD . Similarly, node C and E report the aggregated activeness information in the next cycle, and the cluster head detects TR senders from the received signal. In the polling phase the cluster head polls the identified nodes based on the polling list. Calculation of a polling schedule is beyond the scope of this paper.

IV. P ROPOSED S CHEME

A reporting tree should be constructed in consideration of interference by non-child nodes. As explained above, all equidistant nodes transmit TR/NTR signals at the same time and their signals should be of equal strength at their parents. However, if nodes having different parents are close to each other, the TR/NTR of one of the nodes may reach the other’s parent, causing interference. For example, T RE may reach node B, making it difficult for B to detect T RA (Fig. 4).

Similarly to the OSPCF, the proposed scheme presumes that all nodes are assigned with unique TR/NTR pairs. The assignment can be done when a node is first associated with the cluster head. Nodes are organized into a reporting tree, which is used to deliver activeness information to the cluster head. Note that a reporting tree can also be used for data delivery, but not necessarily. Unless otherwise stated, any reference to tree-related concepts such as level or parents is based on a reporting tree in the rest of the paper. The details of building a reporting tree will be given in Section IV-B. We further assume that a node knows its level and TR/NTR pairs of all its descendent nodes. This information can be set when the reporting tree is constructed, as described in Section IV-B. A. Overview

TRA TRE (interfere)

Fig. 4.

E

B

B

C

CH

D

CH

Inactive node

D Active node detection phase Q:3

Q:2 TRA NTRD

Cycle for level=3

Fig. 3.

Interference due to non-child nodes

Active node

C

CH

A

E

A

Nodes

B. Reporting Tree

Polling phase

Q:1 TRB TRA NTRD

Cycle for level=2

POLL NTRC TRE TRB TRA NTRD

DATA

Cycle for level=1

Overview of the proposed scheme

Fig. 3 shows the overall operation of the proposed scheme, which consists of two phases: active node detection phase and polling phase. The active node detection phase is composed of a number of cycles that correspond to levels of the reporting tree. In each cycle, the cluster head broadcasts a QUERY message, which contains the level of nodes that are to report their activeness in the cycle. Referring to the figure, the cluster head broadcasts a QUERY message with level 3. Upon receiving the message, the level 3 nodes, A and D, send their T RA and N T RD according to their activeness. Note that the signals may be transmitted more than once to combat

Observing that the interference becomes serious as the signals from non-child nodes are stronger, we pose two constraints on constructing a reporting tree; first, every node adjusts its transmission power so that its received signal strength is, say, RSS at its parent; second, a node chooses the closest lower-level node as its parent. Here, closeness is determined not by the physical distance but by the received signal strength at the lower level nodes. With these constraints we can ensure that the signal power of a child node is always stronger at its parent node than that of a non-child node. Consequently, the effect of signals from non-child nodes can be minimized. Referring again to Fig. 4, the signal strength of T RE is always weaker than that of T RA . The procedure of constructing a reporting tree is as follows. First, all nodes whose signal strengths are equal to or stronger than RSS at the cluster head become the level 1 nodes. Similarly, all the remaining nodes whose signal strengths are equal to or stronger than RSS at one of the level 1 nodes become the level 2 nodes. According to the constraints given above, a level 2 node chooses the closest level 1 node as its parent. This procedure is recursively performed until all nodes determine their parents. Subsequently, all nodes report their levels and parents to the cluster head, which then assigns each node with a unique TR/NTR pair. By overhearing

Ratio

those messages, a node can overhear and remember the IDs and TR/NTR pairs of its descendent nodes. After finishing tree construction, nodes continuously adjust their transmission power so that their TR/NTR signals reach their parent nodes with power RSS. Note that power equalization is necessary only for TR/NTR signals; data signals are not subject to power control.

0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00

Eb/N0 = 0 Eb/N0 = 10 Eb/N0 = 20

4

8

12 16 # of child nodes

V. P ERFORMANCE E VALUATION

A. Detectability In this section, we simulate one cycle of the active node detection phase. Specifically, several child nodes send their TR/NTR signals to their parent. At the same time, some nonchild nodes also send their signals that are weaker than that of the children. We then measure how accurately the parent can detect the TRs and NTRs of the child nodes by our scheme. Note that we deal only with baseband signals for simplicity; up/down conversion and bandpass filtering are omitted. Also, all signals are represented as a sequence of complex numbers (symbols), assuming that analogue signals are sampled at a certain rate. The simulation procedure is as follows. First, each child and non-child node generates its TR or NTR symbol array using BPSK modulation. The symbol array is then converted to an impulse train sequence by applying Nyquist filter [17]. To simulate a realistic channel, the sequence is contaminated by two-way Rayleigh-fading and Additive White Gaussian Noise [18]. Because signals from nodes can be misaligned at the receiver side, a random number of zero-valued symbols are prepended to the sequence. If it is sent from a non-child node, we randomly pick a real number between 0 and 0.99 and multiply it to all symbols of the sequence to weaken the signal strength. The cluster head then combines all the sequences and proceeds to detect TRs and NTRs as specified in Section III. We set the total number of nodes to 32, and changed the number of child nodes in the range of 4 to 28. Non-child nodes are randomly selected from the remaining nodes. Fig. 5 shows the average false negative ratio and average false positive ratio. False negative means failing to detect a TR, whereas false positive is falsely detecting a TR when its NTR was actually sent. It is obvious that the detection accuracy improves as the channel quality becomes better. In addition, as the number of child nodes grows, both the false negative and false positive ratio also increases. This indicates that the interference caused by other child nodes is greater than those caused by non-child nodes, possibly because of stronger signal strength. Taking into account that the Eb /N0 in a typical office environment is 10 dB [19], we set the false negative ratio and false positive ratio to 0.02 and 0.05 in the rest of performance evaluation.

24

28

(a) False negative ratio

0.15 Ratio

In this section we first investigate the accuracy of TR detection under a realistic channel model. Based on the result, we compare the average polling period with other schemes, which is defined as the time required to update the polling list and gather data packets from all active nodes.

20

Eb/N0 = 0 Eb/N0 = 10 Eb/N0 = 20

0.10 0.05 0.00 4

8

12

16 20 # of child nodes

24

28

(b) False positive ratio Fig. 5.

Detectability test result

B. Polling Period In this section we compare the performance of the proposed scheme with two other existing algorithms by measuring the average polling period. The first algorithm simply polls every node assuming that all nodes are active. This algorithm will be referred to as the blind algorithm. The second algorithm is the two-step polling introduced in Section II. Note that all methods employ the online polling algorithm [6] to calculate polling schedule for fair comparison; that is, given the same polling list, all three algorithms yield the same result. Thus, difference in performance results only from the efficiency and accuracy of a polling list management scheme. Moreover, we also adopt the polling model considered in [6]; each time the cluster head broadcasts a polling message, a node specified in the message delivers only one packet to the next hop. All packets are presumed to be perfectly delivered except TR/NTR signals. Note that this impractical assumption is a conservative choice for the proposed scheme because the proposed scheme may have to run multiple times until all data is gathered. Note that the polling interval, time between two successive POLL messages, should be long enough for a maximum-length packet to be transmitted. Considering the POLL message transmission time, the maximum WLAN MAC frame length (2304 octets), the interframe spaces, and the corresponding ACK message, we set the polling interval to 6 msec. The cycle interval is the time required for a cycle in the active node detection phase of the proposed scheme. It includes QUERY message transmission time, interframe spaces, TR/NTR signal transmission time, plus signal detection time. We assume that the TR/NTR signal transmission is repeated three times per cycle to reduce detection error. Hence, we set the cycle interval to 1.8 msec, based on 0.6 msec specified in [15]. The false

Polling period (msec)

negative ratio and false positive ratio are set to 0.02 and 0.05, respectively.

compared the average polling period of the proposed scheme with two other existing algorithms. The result shows that the proposed scheme performs significantly better than others. ACKNOWLEDGMENT

400

This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency” (NIPA2009-C1090-0902-0004)

300 blind

200

two-step proposal

100

0 0

0.1

Fig. 6.

0.2

0.3

0.4 0.5 0.6 Active node ratio

0.7

0.8

0.9

1

Comparison of the average polling period

Fig. 6 shows the result of the simulation. The blind algorithm yields almost a constant polling period regardless of the active node ratios since it always polls every node. The twostep polling performs better than the blind algorithm because it first determines active nodes by polling a carefully selected subset of nodes. However, this method is not as efficient as the proposed scheme as shown in the figure. The reason is that the two-step polling uses normal data signalling, whereas the proposed scheme exploits orthogonal signalling that allows all equidistant nodes report their activeness at the same time. The proposed scheme outperforms the two-step polling especially when the active node ratio is not high. This is because when the number of active nodes is small, the time required for updating a polling list determines the overall performance. On the other hand, as the nodes become busy all three algorithms yield similar result. Particularly, when all nodes are active, the blind algorithm performs best. The reason is that given all nodes have packets to send, a polling list management schemes of the two-step polling and the proposed scheme merely act as overheads. However, this situation rarely happens in a practical setting. As the number of nodes n grows, the proposed scheme requires O(log n) time since it depends on the maximum level of nodes. On the other hand, the two-step polling requires O(n) time because all nodes need to send data signals and the data signals should not interfere each other. VI. C ONCLUSION In this paper, we proposed an efficient polling list management scheme for intra-cluster communication in heterogeneous networks. The proposed scheme allows the nodes equidistant to the cluster head report their activeness information at the same time using orthogonal signals. These signals are aggregated and forwarded along a reporting tree until they reach the cluster head, which then proceed to detect each individual active node from the signal by calculating correlation. We suggested a method to construct a reporting tree that can minimize interference from non-child nodes. The accuracy of orthogonal signal detection was studied through a simulation under a realistic channel model. Based on the result, we

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