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This paper studies the wireless sensor networks (WSN) application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is...
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Context 1
... 5: Given a sink tree T (u 0 ) with t branches Proof: For each sensor u i with d u i data units, we generate m = d u i virtual-sensors {u 1 i , u 2 i , · · · , u m i } with one data unit each, as illustrated in Figure 3. Among them, u 1 i replaces u i to connect all its original children {u i+1 } and parent u i−1 , and each virtual sensor u j i (j ∈ [2, m]) becomes the new children of u i−1 . ...
Context 2
... first assume all direct children of a sink have only one unit of data. Then, it is not difficult to calculate that Algorithm 2 takes max(2DN (u 1 ) − 1, DN (u 0 ) − 1) time slots to collect all the data in the sensor network, since each sensor u i in Figure 3(a) can be converted to d u i vir- tual sensors and each virtual-sensor in the new tree has the same amount of data. Then Theorem 4 applies directly. ...
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Citations
... The problem of minimizing the scheduling length for raw-data convergecast, using the interference graph, is proved to be NP-complete by a reduction from the known hard problem, Partition Problem [33]. The optimum lower bounded max(2n − 1 , N) is obtained by the algorithm of [34], where represents the number of nodes in the network and represents the maximum number of nodes in a top-subtree (subtree that has a child of the sink as its root). But this optimum is for radios with fixed bandwidth. ...
... The problem of minimizing scheduling length for raw-data convergecasts, taking into consideration the interference graph, is proven to be NP-complete by reduction from the known hard problem Partition Problem [2]. The optimum lower bounded max(2n k -1 , N) is achieved by the algorithm in [17]. However, this optimum is for radios with fixed bandwidth. ...
Many applications in Wireless Sensor Networks (WSNs) require collecting massive data in a coordinated approach. To that end, a many-to-one (convergecast) communication pattern is used in tree-based WSNs. However, traffic near the sink node usually becomes the network bottleneck. In this work, we propose an extension to the 802.15.4 standard for enabling wider bandwidth channels. Then, we measure the speed of data collection in a tree-based WSN, with radios operating in these wider bandwidth channels. Finally, we propose and implement Funneling Wider Bandwidth (FWB), an algorithm that minimizes schedule length in networks. We prove that the algorithm is optimal in regard to the number of time slots. In our simulations and experiments, we show that FWB achieves a higher average throughput and a smaller number of time slots. This new approach could be adapted for other relevant emerging standards, such as WirelessHART, ISA 100.11a and IEEE 802.15.4e TSCH.
... [6] Consequently, a routing protocol for WSNs should not only facilitate the data transmission, but also consider sensor constraints and provide Quality of Service (QoS) requirements since routing decisions can impact the whole network. [7] Recently, a new routing paradigm, known as Opportunistic Routing (OR) also called Any-Path Routing, was proposed to mitigate the impact of link quality variations. [8] This is done by exploiting the broadcast nature of the wireless medium in an efficient manner such that one transmission can be overheard by multiple nodes. ...
Energy efficiency and Quality of Service (QoS) providing are known to be critical design concerns in routing protocols for Wireless Sensor Networks (WSNs). Recent studies, demonstrate that Opportunistic Routing (OR) can greatly improve the performance of WSNs by exploiting the broadcast nature of the wireless medium. In this paper, we propose a new QoS aware and Energy efficient Opportunistic Routing protocol (QEOR) to efficiently routing data under QoS and energy constraints for WSNs. QEOR uses a new multi-metric QoS based candidate selection method in order to accurately select and prioritise the candidate forwarders. The selection is focused on a QoS function that takes into consideration the reliabilty of buffers and links, while the prioritisation is established according to transmission delays. To achieve an obvious improvement on the energy consumption, QEOR uses an energy efficient coordination method and an implicit ACKnowledgement scheme for collision and redundancy avoidance. Simulation results show that QEOR provides best performances as compared to other OR protocols.
... Additionally, the solution for solving an integer linear programming problem in [Xu et al. 2010] costs much time, which is prohibitive for a large system. Packets in [Song et al. 2006] owns the same properties of a sampling task we discuss in the paper. Release time and deadline of a packet represents begin time and end time, respectively. ...
... The difference is that a packet reports one unit of data, not the data which is sampled over a time interval continuously. Thus, the methods in [Song et al. 2006] work well for the discrete point sampling tasks, not the interval sampling tasks. The most related work to ours are [Tavakoli et al. 2010] and [Fang et al. 2013]. ...
Data sharing amongst multiple sampling tasks significantly reduces energy consumption and communication cost in low-power WSNs. Conventional proposals have already scheduled the discrete point sampling tasks to decrease the amount of sampled data. However, less effort has been done for the applications which generate continuous interval sampling tasks. Moreover, most of pioneering work limits its view to schedule sampling intervals of tasks on a single sensor node, and neglects the process of task allocation in WSNs. Therefore, the gained efforts in the prior work cannot benefit a large-scale wireless sensor network because the performance of a scheduling method is sensitive to the strategy of task allocation. Broadening the scope to an entire network, this paper is the first work to maximize data sharing amongst continuous interval sampling tasks by jointly optimizing task allocation and scheduling of sampling intervals in WSNs. First, we formalize the joint optimization problem and prove it NP-hard. Second, we present COMBINE operation which is the crucial ingredient of our solution. COMBINE is a 2-factor approximate algorithm for maximizing data sharing amongst overlapping tasks. Furthermore, our heuristic named CATS is proposed. CATS is 2-factor approximate algorithm for jointly allocating tasks and scheduling sampling intervals so as to maximize data sharing in the entire network. Extensive empirical study is conducted on a testbed of 50 sensor nodes to evaluate the effectiveness of our methods. Besides, the scalability of our methods is verified by using the widely-used simulation tool, i.e., TOSSIM. The experimental results indicate that our methods successfully reduce the volume of sampled data and decrease the energy consumption significantly.
... Research has shown that raw-data convergecast have been investigated and studied in the literature [8], [17], [18], and [19]. The authors in [8], in order to reduce the schedule length for a TDMA single channel network, proposed a distributed time slot assignment scheme. ...
The concept of data distribution within cluster of sensor nodes to the source sink has resulted to intense research in Wireless Sensor Networks (WSNs). In this paper, in order to determine the scheduling length of packet distribution, a tree-based network topology is constructed indicating the distribution of various sensor nodes within a specific coverage area (CA i ). To evaluate the performance of various channel assignment methods; Receiver-Based Channel Assignment (RBCA), Tree-Based Multichannel Protocol (TMCP), and Capacitated Minimal Spanning Tress (CMSTs), time slot assignment scheme is used in developing the various channel assignments. The performance of packet distribution based on the assignment schemes are evaluated using appropriate simulation tool for the tree-based network topology.
... The CSMA/CA scheme is implemented networkwide, whereas the TDMA scheme is used to allocate additional transmission opportunities to nodes near the sink. Another work that also addresses the many-to-one traffic pattern is a time-optimum packet scheduling algorithm described in [37]. The algorithm can minimize message transfer delay in a tree topology and enables nodes to adjust duty cycles locally. ...
... Both the time-optimum scheduling algorithm [37] and funneling-MAC [36] may not yet be able to support missioncritical applications. In particular, although the algorithm can determine optimal delay, some applications prefer guaranteed performance to fast data delivery. ...
... Raw-data converge cast has been studied in [1], [12], [13], and [14], where a distributed time slot assignment scheme is proposed by Gandham et al. [1] to minimize the TDMA schedule length for a single channel. ...
... A study along this line with the objective to minimize the maximum latency is presented by Pan and Tseng [15], where they assign a beacon period to each node in a Zigbee network during which it can receive data from all its children. For raw-data convergecast, Song et al. [12] presented a time-optimal, energy-e_cient packet scheduling algorithm with periodic tra_c from all the nodes to the sink. Once interference is eliminated, their algorithm achieves the bound. ...
... Song et al. [12] extended the previous work and proposed a Time-based MAC protocol for highdata-rate WSNs in [16]. Tree MAC considers the differences in load at different levels of a routing tree and assigns time slots according to the depth, i.e., the hop count, of the nodes on the routing tree, such that nodes closer to the sink are assigned more slots than their children in order to mitigate congestion. ...
In a network organised as a tree how fast the data can be collected is a fundamental objective of this paper. To address this, a number of different techniques are explored and evaluated using realistic simulation models under the many-to-one communication paradigm known as converge cast. Use of TDMA scheduling gives better performance in case of many to one communication. Channel assignment methods such as BFS time slot assignment, Local time slot assignment and multichannel scheduling algorithm Joint Frequency time slot scheduling for moderate size networks of about 100 nodes, by using multiple frequencies are implemented. Performance of these algorithms is evaluated using JProwler simulator. The data rate for each of these algorithms is calculated using simulation. For moderate size networks of about 100 nodes, the use of multi-frequency scheduling can suffice to eliminate most of the interference.
... CMAC first uses anycast to wake up forwarding nodes, and then converges gradually from route-suboptimal any cast with unsynchronized duty cycling to route-optimal unicast with synchronized scheduling. Time-Optimum Packet Scheduling for Many-to-One Routing in presented in [11]. In the proposed packet scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also mitigated. ...
... The convergecast transmits a large burst of packets within a period to the central manager. Two kinds of convergecast, aggregated data and raw data, have been studied in [11][12][13] for aggregated data and in [14][15][16] for raw data. For many industrial applications, all raw data should be sent to the central manager for low correlation between the data. ...
... Most of existing algorithms aim to minimize the transmission delay and eliminate interference by time sharing reuse. The scheduling problem required to complete convergecast has been studied in [11][12][13] for aggregated data and in [14][15][16] for raw data. ...
Most applications of industrial wireless sensor networks (IWSNs) should converge process data generated by each node to the central manager. The data collection operation results in an important communication primitive referred to as convergecast. Convergecast is a many-to-one communication paradigm as a critical functionality deployed for industrial monitoring and control. Delaying of process data may degrade the overall control performance and even lead to the malfunction of industrial applications. Therefore, timeslot and channel resources should be scheduled efficiently for real-time communication. This paper is interested in determining a TDMA schedule that minimizes the number of timeslots and completes convergecast with a limited number of channels. In order to achieve the lower bound derived by theoretical analysis, we proposed a source aware scheduling algorithm for general network. For IWSNs with a fixed number of available channels, we present a source aware scheduling algorithm with constrained channel. According to simulation results, we demonstrate that the performance of our algorithm is close to the lower bound on latency with a limited number of channels. Our algorithm is also scalable for schedules with multiple packets and specific transmission latency of a single packet.
... In [7], we experimentally investigated the impact of transmission power control and multiple frequency channels on the schedule length, while the theoretical aspects were discussed in [9], where we proposed constant factor and logarithmic approximation algorithms on geometric networks (disk graphs). Raw-data convergecast has been studied in [1], [12], [13], and [14], where a distributed time slot assignment scheme is proposed by Gandham et al. [1] to minimize the TDMA schedule length for a single channel. The problem of joint scheduling and transmission power control is studied by Moscibroda [5] for constant and uniform traffic demands. ...
... For raw-data convergecast, Song et al. [12] presented a time-optimal, energy-efficient packet scheduling algorithm with periodic traffic from all the nodes to the sink. Once interference is eliminated, their algorithm achieves the bound that we present here; however, they briefly mention a 3-coloring channel assignment scheme, and it is not clear whether the channels are frequencies, codes, or any other method to eliminate interference. ...
We scrutinize the following fundamental consideration a number of different techniques using realistic simulation models under the many-to-one communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling with transmission power control to diminish the effects of interference, and show that while power control helps in reducing the schedule length under a single frequency, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the schedule length when interference is utterly eliminated, and propose algorithms that achieve these bounds. We also evaluate the performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, the use of multi frequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited by interference but by the topology of the routing tree. To this end, we construct degree-constrained spanning trees and capacitated minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities. Lastly, we evaluate the impact of different interference and channel models on the schedule length.
