階層式叢集拓樸架構具有多輸入多輸出技術應用於無線感測網路

Hierarchical Cluster Topology Architectures with MIMO Technology for Wireless Sensor Networks

黃拓景(Tuo-Jing Huang)

指導教授 ： 陳永隆

國立臺中科技大學/資訊與流通學院/資訊工程系碩士班/碩士(2017年)

摘要

隨著資訊科技越來越進步，電腦和人類的生活越來越密切，在我們的生活環境中，充滿了感測元件，這些感測元件能透過無線網路進行鏈結傳輸，感測並且收集與我們生活環境有關的資料，我們稱這樣的網路架構為無線感測網路(Wireless Sensor Networks)。在無線感測網路中，感測節點的工作是收集環境的資料並將資料傳送到目的地，不管是收集資料或是傳送資料都需要耗費能量，但感測元件的電量有限並且由於隨機分佈的關係造成不易管理網路中的所有感測元件，因此如何節省節點的電量提高整體網路的能量效率是一項重要的研究議題。為了提高資料的傳輸品質，本研究使用合作式多重輸入多重輸出(Cooperative Multi-Input Multi-Output, CMIMO)技術，減少雜訊干擾所帶來的影響並提升網路的吞吐量(Throughput)，透過在來源與目的中增加數組傳送與接收天線的方式，利用多個空間串流(Spatial stream)傳送資訊，提高資料的傳輸品質。為了將MIMO技術應用無線感測網路中，以減少資料在傳送時雜訊干擾所造成的影響，我們將感測節點加入合作節點集合中，利用集合中的節點進行合作式MIMO傳輸，提升無線感測網路的傳輸品質。
本研究提出了兩種合作式MIMO叢集式拓樸架構分別為改善叢集架構具有合作式多輸入多輸出技術和最佳轉傳(Improved Cluster Architecture with Cooperative Multi-Input Multi-Output Technology and Optimal Relay, ICACMIMOOR)和階層式叢集架構具有合作式多輸入多輸出技術和最佳轉傳(Hierarchical Cluster Architecture with Cooperative Multi-Input Multi-Output Technology and Optimal Relay, HCACMIMOOR)，此外我們會在後續文章中將本篇論文所提出的兩種合作式MIMO技術與[1]所提出的Multi-Channel Cooperative Multi-Input Multi-Output (MCCMIMO)進行比較。在ICACMIMOOR中，我們在合作式MIMO叢集式架構中，加入Energy-efficient Beaconless Geographic Routing (EBGR)演算法，計算中繼轉傳叢集的數量，不但能夠降低轉傳次數而且也能減少因為不必要的叢集傳輸所造成的能量消耗。為了能有效避免ICACMIMOOR在多次轉傳時造成傳送叢集消耗過多的能量，本研究提出HCACMIMOOR架構，在HCACMIMOOR中，我們將來源叢集與其1-hop轉傳叢集視為同一個叢集，再來源端中，將收集到的資料由叢集頭傳送給1-hop轉傳叢集的合作節點，由1-hop轉傳叢集進行合作式MIMO傳輸，減少來源叢集因為傳送資料所造成的能量消耗。在MCCMIMO架構中，有兩項參數會影響節點成為叢集頭。第一因素是節點的剩餘能量，由於叢集頭的工作除了接收叢集成員所傳送之資料外，還要將已收集之資料進行結合後傳送至合作節點，導致擔任叢集頭之節點能量迅速消耗，因此選擇剩餘能量最高的節點擔任叢集頭，能夠有效增加所有節點的存活時間。另一因素取決於節點與鄰近節點間的平均距離，由於傳送資料所消耗的能量會受到傳輸距離的影響，若距離越長則所消耗的能量越大，如果叢集頭的位置距離鄰近節點太遠，會造成叢集內部的節點能量消耗過快，導致叢集快速死亡，因此節點的位置也被列入是否能當選叢集頭考量的因素。
探討本研究所提出的兩種合作式MIMO叢集式拓樸架構ICACMIMOOR與HCACMIMOOR之比較，在能量效率方面，ICACMIMOOR、HCACMIMOOR與MCCMIMO比較每回合的節點剩餘能量總和中，在第200回合時，MCCMIMO的節點剩餘能量總和為164J、ICACMIMOOR為230J與HCACMIMOOR為230.4J，因此我們提出的架構能有效提高能量效率並且延長網路的生命週期。

關鍵字

無線感測網路 ； 階層式叢集架構 ； 最佳中繼轉傳 ； 合作式MIMO

並列摘要

With information technology getting more and more progress, computer and human life is getting closer and closer, in our living environment, filled with sensing elements, these sensing elements can be linked through the wireless network transmission, monitoring and sensing to collect information about our living environment, we say this kind of network architecture is Wireless Sensor Networks. In the wireless sensor network, the sensing node's work is to collect information about the environment and transfer the data to the destination, whether it is to collect data or send data both need to consume energy, but the sensing component of the power is limited and due to random distribution So that it is not easy to manage all the sensing elements in the network, so how to save the power of the nodes to improve the overall network Energy efficiency is an important research topic. In order to improve the transmission quality of data, this study uses Cooperative Multi-Input Mult-output(CMIMO) technology, to reduce noise interference and improve the throughput of the network. This method is to increase the transmission quality of the data by increasing the number of transmission and reception antennas in the source and destination and using multiple spatial streams to transmit information. In order to apply the MIMO technology to the wireless sensor network to reduce the influence of the noise in the transmission, we add the sensing nodes to the cooperative node set, use the nodes in the cluster to cooperatively MIMO transmission, improve the transmission quality of Wireless Sensor Networks.
In this paper, we proposed two kinds of cooperative MIMO cluster topology architectures, which are Improved Cluster Architecture with Cooperative Multi-Input Multi-Output Technology and Optimal Relay (ICACMIMOOR) and Hierarchical Cluster Architecture with Cooperative Multi-Input Multi-Output Technology and Optimal Relay (HCACMIMOOR). In addition, we will compare the two kind of cooperative MIMO technologies in this paper proposed and Multi-Channel Cooperative Multi-Input (MCCMIMO) which we refer to the author proposed.
In MCCMIMO which proposed by [1], there are two factors that affect the node to be a cluster header. The first factor is the residual energy of the node. Since the work of the cluster head not only receives the information transmitted by the cluster members, it also sends the collected data to the cooperative node, which leads to the rapid consumption of the nodes as the node head, so the node with the highest remaining energy is chosen as the cluster head, which can effectively increase the survival time of all nodes. Another factor depends on the average distance between the node and the neighboring nodes. Since the energy consumed by the transmitted data is affected by the transmission distance, if the position of the cluster head is too far from the adjacent nodes, causing the nodes in the cluster consume energy too fast, resulting in rapid death of the cluster, so the location of the node is also a factor of consideration.
In ICACMIMOOR, we add Energy-efficient Beaconless Geographic Routing (EBGR) algorithms in a cooperative MIMO cluster architecture to calculate the number of relay transfer clusters, which not only reduces the number of transfers but also reduces the energy caused by unnecessary cluster transmissions consumption.
In order to effectively avoid ICACMIMOOR in the number of times when the cluster caused by excessive consumption of energy, this study proposed HCACMIMOOR architecture. In HCACMIMOOR, we treat the source cluster as its 1-hop transition cluster as the same cluster. In source side, the collected data is sent by the cluster head to the cooperative node of the 1-hop transition cluster, than cooperative MIMO transmission is performed by 1-hop transfer clusters, to reduce the energy consumption of the source cluster due to the transmission of data.
At the last, compare the two kinds of cooperative MIMO technologies in this paper proposed ICACMIMOOR, HCACMIMOOR and MCCMIMO which we refer to the author proposed. In terms of energy efficiency, ICACMIMOOR, HCACMIMOOR and MCCMIMO compare the node remaining energy sum in each round, at the 200th round, MCCMIMO node residual energy sum of 164J, ICACMIMOOR 230J and HCACMIMOOR 230.4J, so we proposed the structure can be effective Improve energy efficiency and extend the lifecycle of the network.

並列關鍵字

Wireless sensor networks ； hierarchical cluster architecture ； optimal relay ； cooperative MIMO

參考文獻

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