無線傳感器網絡

傳感器基礎知識

由於超大規模集成電路 (VLSI) 以及微機電系統科技 (MEMS technology) 等硬件基礎以及radio frequency (RF) 技術的進步，使得傳感器的發展愈來愈快。

傳感器具備的優點：

1. 能夠放置在任何環境，任什麼時候間均可以工做，而且不須要太多的人力來進行管理。
2. 具備更好的容錯能力，局部出現故障仍然能較好的完成工做。
3. 獲取的數據更精確。經過多個傳感器獲取的信息更加可靠準確。
4. 成本低以及容易部署。

Due to WSNs’reliability, self-organization, flexibility, and ease of deployment, their existing and potential applications vary widely. As well, they can be applied to almost any environment, especially those in which conventional wired sensor systems are impossible or unavailable, such as in inhospitable terrains, battlefields, outer space, or deep oceans.

傳感器用於通訊耗費的資源比用於感知和計算花費的資源多[1,12]：It is reported that the energy consumed by communication is much higher than that for sensing and computation; in fact, this actually dominates the total energy consumption in WSNs. Furthermore, in most WSNs, power for transmission contributes to a majority of the total energy consumed for communication and the required transmission power grows exponentially with the increase of transmission distance. Therefore, reducing the amount of traffic and distance of communications can greatly prolong the system’s lifetime.

無線傳感器網絡與傳統無線自組織網絡的區別[1]

無線傳感器網絡的分類

由於不一樣的傳感器使用的環境不一樣，相應的技術要求也不一樣，所以傳感器經常是面向應用來設計的，因此不一樣無線傳感器網絡的架構 (architectures)、協議 (protocols) 以及算法也每每不同。雖然如此，不一樣的傳感器網絡仍然具備一些共同的特色，通常有如下幾種劃分方式[1]：

1. 根據WSNs節點到基站的距離，能夠劃分爲單跳 (single-hop, also known as nonpropagating) 和多跳 (multihop or propagating) 系統。在單跳系統中，全部的傳感器節點直接把數據傳輸給基站，在多跳系統中數據須要通過中間傳感器節點才傳到基站。較小的傳輸功率可能會因爲跳數增長和再傳輸機率增大而致使功率消耗過大[9]，不過文獻[10]中提供了一種方法能夠對多跳系統傳輸的能量進行估計。Single-hop networks have much simpler structure and control and fit into the applications of small sensing areas; multihop networks promise wider applications at the cost of higher complexity.

更多有關單跳和多跳系統[1]：

As reported in Rappoport [7], large-scale propagation follows as exponential law to the transmitting distance (usually with exponent 2 to 4 depending on the transmission environment). It is not difficult to show that power consumption due to signal transmission can be saved in orders of magnitude by using multihop routing with short distance of each hop instead of single-hop routing with a long range of distance for the same destination. And the majority of existing WSN literature is based on multihop ad hoc architectures.

1. 基於傳感器節點密度和數據依賴性，WSNs能夠劃分爲聚合的和非聚合的網絡。在非聚合系統中，來自每一個節點的全部數據將被髮送到目的地，中間節點的計算負載相對較小，系統能夠達到高精度。可是，隨着網絡規模的擴大，整個系統的總流量負載可能會迅速增長，通訊將消耗更多的能量，會產生更多的衝突和/或擁塞，致使高延遲。Therefore, the nonaggregating scheme is suitable for systems that have less node density, sufficient capacity, and/or in which extremely high accuracy is
   demanded by end users. 而在密集分佈的網絡中，傳感器節點一般位於鄰近節點附近。所以，來自多個源的信息可能高度相關，而且能夠在中間節點上執行聚合函數以消除數據冗餘。這樣，系統的交通負荷就會大大下降，而且能夠得到大量的通訊能量。可是，中間節點將執行計算函數，這可能須要更大的內存。
2. 根據傳感器節點的分佈，WSNs能夠是肯定性的或動態的。在肯定性系統中，傳感器節點的位置是固定的或預先計劃的。該系統的控制更簡單，實現也更容易。可是，該方案僅適用於可以提早獲取和規劃傳感器節點位置信息的有限系統。然而，在許多狀況下，傳感器節點的位置是不可提早得到的，例如在偏遠地區隨機丟棄的節點。動態方案具備更強的可擴展性和靈活性，但須要更復雜的控制算法。
3. 根據控制方案，WSNs能夠是不可自我配置的，也能夠是自我配置的。在前一種機制中，傳感器節點不能自行組織，而是依靠中央控制器向它們提供命令並收集信息。該方案只能用於小型網絡。然而，在大多數WSNs中，傳感器節點能夠自行創建和維護鏈接，協同完成傳感和控制任務。這種自配置方案更適合大型系統執行復雜的監視任務和信息收集和傳播。儘管自我配置系統比非自我配置系統更復雜，但在實際應用中更實用，特別是當網絡規模變得很是大時。然而，它們提出了許多挑戰和有待進一步探討的開放問題。
   總結見下表[1]。
   

性能評估方法

無線傳感器網絡是一種特殊的自組織網絡（Ad hoc networks），和自組織網絡同樣面臨着能量有限（energy constraints）以及路由選擇（routing）的挑戰，其中能量有限（energy constraints）是無線傳感器最大的挑戰。

有不少指標能夠用來評估傳感器網絡的性能狀況，其中主要有：

1. Energy efficiency/system lifetime. The sensors are battery operated, rendering energy a very scarce resource that must be wisely managed in order to extend the lifetime of the network[2].
2. Latency. Many sensor applications require delay-guaranteed service. Protocols must ensure that sensed data will be delivered to the user within a certain delay. Prominent examples in this class of networks are certainly the sensor-actuator networks.
3. Fault tolerance. Robustness to sensor and link failures must be achieved through redundancy and collaborative processing and communication.
4. Scalability. Because a sensor network may contain thousands of nodes, scalability is a critical factor that guarantees that the network performance does not significantly degrade as the network size (or node density) increases.
5. Transport capacity/throughput. Because most sensor data must be delivered to a single base station or fusion center, a critical area in the sensor network exists, whose sensor nodes must relay the data generated by virtually all nodes in the network. Thus, the traffic load at those critical nodes is heavy, even when the average traffic rate is low. Apparently, this area has a paramount influence on system lifetime, packet end-to-end delay, and scalability.

提升傳輸效率的方法

能夠利用下面幾種方式來提升傳感器的能量利用效率[1]：

• 首先，能夠在集羣中應用分佈式源編碼的形式進行數據壓縮，以減小要傳輸的數據包數量。First, data compression in the form of distributed source coding is applied within a cluster to reduce the number of packets to be transmitted.
• 其次，數據中心化的屬性使傳感器節點的標識 (例如地址) 變得用處不大，然而在不少場景中咱們比較關注某些區域的數據特色，這時就要去除中心化，利用分佈式處理數據的方法。Second, the data-centric property makes an identity (e.g., an address) for a sensor node obsolete. In fact, the user is often interested in phenomena occurring in a specified area[3], rather than in an individual sensor node.
• 此外，也能夠利用廣播樹和多播樹策略來提升能量利用效率（該方法缺點：會致使較高的計算複雜度）。Another strategy to increase energy efficiency is to use broadcast and multicast trees.
• 最後，引入傳感器睡眠機制減小電量消耗[11]。The exploitation of sleep modes is imperative to prevent sensor nodes from wasting energy in receiving packets unintended for them. For example, one option is to use coordinated policy for deciding which node will go to sleep while the connectivity in the node is maintained[15].

建模

通常對傳感器建模時考慮傳感器可能處於四種狀態：傳輸信號(transmission), 信號檢測(reception), 信號接收(listening), 睡眠(sleeping)。其中，

• Transmission: processing for address determination, packetization, encoding, framing, and maybe queuing; supply for the baseband and RF circuitry.
• Reception: Low-noise amplifier, downconverter oscillator, filtering, detection, decoding, error detection, and address check; reception even if a node is not the intended receiver.
• Listening: Similar to reception except that the signal processing chain stops at the detection.
• Sleeping: Power supply to stay alive.

傳感器網絡存在的技術挑戰和解決方法

技術挑戰

目前主要的挑戰問題[1]：

1. Massive and random deployment. Most WSNs contain a large number of sensor nodes (hundreds to thousands or even more), which might be spread randomly over the intended areas or are dropped densely in inaccessible terrains or hazardous regions. The system must execute self-configuration before the normal sensing routine can take off.
2. Data redundancy. The dense deployment of sensor nodes leads to high correlation of the data sensed by the nodes in the neighborhood.
3. Limited resources. WSN design and implementation are constrained by four types of resources: energy, computation, memory, and bandwidth. Constrained by the limited physical size, microsensors could only be attached with bounded battery energy supply. Moreover, WSNs usually operate in an untethered manner, so their batteries are nonrechargeable and/or irreplaceable. At the same time, their memories are limited and can perform only restricted computational functionality.
   The bandwidth in the wireless medium is significantly low as well.
4. Ad hoc architecture and unattended operation. The attributes of no fixed infrastructure and human-unattended operation of such networks require the system to establish connections and maintain connectivity autonomously.
5. Dynamic topologies and environment. On the one hand, the topology and connectivity of WSNs may frequently vary due to the unreliability of the individual wireless microsensors. For example, a node may fail to function because of exhaustion of power at any time without notification to other nodes in advance. As well, new nodes may be added randomly in an area without prior notification of existing nodes. On the other hand, the environment that the WSNs are monitoring can also change dramatically, which may cause a portion of sensor nodes to malfunction or render the information they gather obsolete.
6. Error-prone wireless medium. Sensor nodes are linked by the wireless medium, which incurs more errors than their wired counterpart. In some applications, the communication environment is actually noisy and can cause severe signal attenuation.
7. Diverse applications. WSNs could be used to perform various tasks, such as target detection and tracking, environment monitoring, remote sensing, military surveillance, etc. Requirements for the different applications may vary significantly.
8. Safety and privacy. Safety and privacy should be an essential consideration in the design of WSNs because many of them are used for military or surveillance purposes. Denial of service attacks against these networks may cause severe damage to the function of WSNs. However, security seems to be a significantly difficult problem to solve in WSNs because of the inevitable dilemma: WSNs are resource limited and security solutions are resource hungry. Indeed, most existing communication protocols for WSNs do not address security and are susceptible to adversaries [9].
9. QoS concerns. The quality provided by WSNs refers to the accuracy with which the data reported match what is actually occurring in their environment. Different from others, accuracy in WSNs emphasizes the characteristic of the aggregated data of all sources instead of individual flows. One way to measure accuracy is the amount of data. Another aspect of QoS is latency. Data collected by WSNs are typically time sensitive, e.g., early warning of fires. It is therefore important to receive the data at the destination/control center in a timely manner. Data with long latency due to processing or communication may be outdated and lead to wrong reactions.

傳感器的協做問題

由於有時候須要對一個移動的目標進行數據採集，好比說移動目標地理位置信息，不少時候要想準確獲得這樣的信息須要多種不一樣傳感器之間協做，由於單個傳感器採集的數據有時會出錯以及誤報。如今能夠採用分佈式計算技術來解決這一問題[1]：

These capabilities are now being extended to include high-speed wireless and fiber networking with distributed computing. As the Internet protocol (IP) technologies continue to advance in the commercial sector, the military can begin to leverage IP formatted sensor data to be compatible with commercial high-speed routers and switches. Sensor data from theater can be posted to high-speed networks, wireless and fiber, to request computing services as they become available on this network. The sensor data are processed in a distributed fashion across the network, thereby providing a larger pool of resources in real time to meet stringent latency requirements. The availability of distributed processing in a grid-computing architecture offers a high degree of robustness throughout the network. One important application to benefit from these advances is the ability to geolocate and identify mobile targets accurately from multiaspect sensor data.

目前協做存在的不足：The limitation is with the communication and available distributed computing.

多跳決策問題

無線傳感器網絡一般在很寬的區域內包含大量的傳感器節點，基站可能遠離無線傳感器。所以，將整個系統劃分紅不一樣的集羣，用多跳短距離數據轉發代替單跳遠程傳輸。這將減小數據通訊消耗的能量，而且在網絡規模增加時具備負載平衡和可伸縮性的優點。這種基於集羣的方法面臨的挑戰包括如何選擇集羣頭以及如何組織集羣。有大量文章介紹瞭如何選擇集羣頭，選擇集羣頭要注意的一個問題是：不只要保證WSNs效率高，並且各個集羣頭的負載要平衡（見文獻[1]7-16）

去除冗餘信息問題

在傳感器通訊過程當中可能存在冗餘信息，去除多餘冗餘信息將顯著提升效率。The most straightforward is duplicate suppression, i.e., if multiple sources send the same data, the intermediate node will only forward one of them. Maximum or minimum functions are also very simple approaches. Heinzelman and colleagues [13] and Julik and coworkers [14] propose a scheme named sensor protocols for information via negotiation (SPIN) to realize traffic reduction for information dissemination. It introduces metadata negotiations between sensors to avoid redundant and/or unnecessary data through the network.

能量補充問題

能量問題是傳感器網絡須要解決的重要問題。能源供應至少能夠用兩種概念上不一樣的方式來解決，第一種方式是爲每一個傳感器節點配置一個 (可再充電) 的能量源，能夠經過兩種途徑: (1)選擇是使用高密度電池 (當前主要方式); (2)使用燃料電池 (full cells)，但目前還不能很好地應用於傳感器上；第二種方式是選擇在環境中獲取能源，好比說太陽能電池、熱能電池。

定位問題

WSNs的部署常常是隨機放置的，與之相關的主要挑戰之一是選擇傳感器的類型和數量並肯定它們的位置。這一任務是困難的，由於有許多類型的傳感器具備不一樣的屬性，如分辨率、成本、精度、大小和功耗。不過這一問題有解決方法：For example, consider determining distance using audio sensors. Because the speed of sound depends greatly on temperature and humidity of the environment, it is necessary to take both measurements into account in order to get the accurate distance. 已有的傳感器定位技術有:VM[17], SeRLoc[18].

傳感器網絡的管理

由於絕大部分傳感器比較廉價，使用時投放量多，範圍廣，而且比較隱蔽，這使得若是去維護傳感器每每成本較高，並且效率很低，因此每每傳感器一經投放就幾乎不多去維護，這些特色使得傳感器必須具有自治能力，也即自我管理能力 (self-managed, including self-organizing, self-healing, self-optimizing, self-protecting, self-sustaining, self-diagnostic) ，這就是咱們稱爲傳感器網絡爲自組織網絡的緣由。

A managed WSN with this has various characteristics can be called an autonomic system[4], which is an approach to self-managed computing systems with a minimum of human interference. The processors in such systems use algorithms to determine the most efficient and cost-effective way to distribute tasks and store data. Along with software probes and configuration controls, computer systems will be able to monitor, tweak, and even repair themselves without requiring technology staff — at least, that is the goal.

傳感器網絡自我管理存在的問題

通常傳統的計算機網絡在設計和部署時考慮到了便於管理員來維護的因素，然而傳感器網絡自己就不多考慮到維護問題，因此傳感器的管理每每是指自我管理，不一樣於傳統計算機網絡的由管理員來管理的特色。對傳感器網絡來講，由於傳感器能量有限，因此傳感器網絡的全部執行的操做必需要求是高效節能的。此外，傳感器網絡在工做過程當中可能會發生故障或者能量耗盡，這致使了網絡的拓撲結構是是不斷動態退化的。

傳感器網絡自我管理的主要體現的方面[1]：

A managed WSN is responsible for configuring and reconfiguring under varying (and, in the future, even unpredictable) conditions. System configuration (「node setup」 and 「network boot up」) must occur automatically; dynamic adjustments need to be done to the current configuration to best handle changes in the environment and itself. A managed WSN always looks for ways to optimize its functioning; it will monitor its constituent parts and fine-tune workflow to achieve predetermined system goals. It must perform something akin to healing — it must be able to recover from routine and extraordinary events that might cause some of its parts to malfunction. The network must be able to discover problems or potential problems, such as uncovered area, and then find an alternate way of using resources or reconfiguring the system to keep it functioning smoothly. In addition, it must detect, identify, and protect itself against various types of attacks to maintain overall system security and integrity. A managed WSN must know its environment and the context surrounding its activity and act accordingly. The management entities must find and generate rules to perform the best management of the current state of the network.

服務管理

傳感器的服務和許多應用軟件的功能模塊有關，傳感器基本的服務包括 感知(sensing)、數據處理(processing)，以及 數據分發(data dissemination)[5]。傳感器管理主要有兩個方面：quality of service (QoS) and denial of service (DoS).

其中，涉及到對WSNs的QoS支持的組成部分主要包括 QoS models，QoS sensing，processing 以及 QoS dissemination [6]. The larger the number of monitored QoS parameters is, the larger the energy consumption and the lower the network lifetime are.

1. QoS model. A QoS model specifies an architecture in which some of the services can be provided in WSNs.
2. QoS sensing. QoS sensing considers the sensor device calibration, environment interference monitoring, and exposure (time, distance, and angle between sensor device and phenomenon).
3. QoS dissemination. Reliable data delivery is still an open issue in the context of WSNs. QoS dissemination in WSNs is a challenging task because of constraints, mainly energy and dynamic topology of WSNs.
4. QoS processing. Processing quality depends on the robustness and complexity of the algorithms used, as well as processor and memory capacities. The way to measure processing performance changes from processor speed to the immediacy and accuracy of the response and energy consumption.

傳感器網絡的安全

目前的研究主要集中在提供最節能的路由。在無線傳感器網絡中，安全有效的路由協議和高效的路由協議做爲攻擊是很是須要的。在無線傳感器網絡中，須要安全和高效的路由協議，好比地陷 (sinkhole)、蟲洞 (wormhole) 和 Sybil 攻擊。另外，無線傳感器網絡中，數據包傳輸經常會遇到丟包 (missing packets)、僞造和篡改、衝突 (Conflicts)、延遲 (Latency)、非法操做 (illegal operation) 等。

蟲洞攻擊是指惡意節點竊聽一個數據包或一系列數據包，經過傳感器網絡將其傳輸到另外一個惡意節點，而後從新播放數據包。

有關安全的保護技術

三種密碼學方法已經被應用於現實系統的安全中：防火牆 (firewalls), 蜜罐技術 (honeypots), 入侵檢測技術 (intrusion detection techniques). 介紹以下[1]：

1. 防火牆：A firewall is a policy enforcement point (node) for a part of a network designed to restrict access from and to that subnetwork. Several classes of firewalls exist: packet filtering according to a particular set of rules; access to particular servers or ports; or application-level firewalls that protect by remembering the state of the network connection. Firewalls still face denial of service (DoS) attacks and they try to address them by filtering suspicious connections. Among the several limitations of firewalls is the fact that they do not protect the network from insider attacks and that filtering can only be done against already known attacks.
2. 蜜罐技術：Honeypots are systems placed on networks specifically for the purpose of being attacked or compromised. Because they are not designed for true use, they exist only to detect and collect information about security attacks. Advantages of honeypots include low false positives; ability to capture unknown attacks; and ability to facilitate interaction with the attacker in order to gain better insights into actions and thinking. Intrusion detection techniques aim at recognizing statistical or pattern irregularities in the incoming or outgoing traffic. The most recent approach to detection of Internet attacks is probabilistic deduction of the IP traceback. Finally, virtual private networks are logical extensions of private networks over insecure channels provided by the Internet.

因爲傳統的密鑰交換技術使用非對稱密碼技術，也稱爲公鑰密碼技術。在無線傳感器網絡中，非對稱密碼技術的問題在於它對於傳感器網絡中的各個節點而言一般計算量太大，於是很難適用。不過，對稱密碼技術須要耗費的計算量小不少，能夠應用於傳感器網絡，可是對稱密碼技術安全的前提是雙方共享一個密鑰，而且在一方給另外一方發送密鑰時沒有被監聽，那麼雙方通訊是安全的。然而，實際中很難保證不被監聽，因此對稱加密相對容易被破解，所以會帶來安全問題。

由於在傳感器網絡中，遠程配置和應用程序代碼更新須要經過移動代碼的注入以及傳播來完成。合法的移動代碼經過幾個節點注入到網絡中，而後在網絡中傳播[16]。保護移動代碼安全的方法有：代碼簽名 (code signing), 沙盒 (sand-boxes), 以及 攜帶證實的代碼 (proof-carrying code).

常見網絡攻擊類型

WSNs一旦部署，惡意攻擊對WSN中用於管理和代碼更新的節點的訪問將產生安全威脅並消耗資源。儘管避免攻擊很困難，但容許在應用程序和系統中修改節點的機制是必要的。在移動代碼入侵技術中，最流行的有四種: 病毒(Virues)、特洛伊木馬(Trojan horses)、緩衝區溢出(buffer overflow) 和 祕密通訊通道(covert communication channels)。

隱蔽通訊信道是由計算機系統中的資源共享引發的。例如，具備高優先級的進程能夠經過干擾或避免干擾進程的時間來將信息傳遞給具備低優先級的進程。

幾種經常使用攻擊方法

攻擊能夠經過多種方式執行，這裏介紹幾種[20]，最明顯的是拒絕服務攻擊，此外還有流量分析，隱私侵犯，物理攻擊等等。對無線傳感器網絡的拒絕服務攻擊的範圍能夠從簡單地干擾傳感器的通訊信道到旨在違反802.11 MAC協議或任何其餘無線傳感器網絡層的更復雜的攻擊[19]。致使網絡拒絕服務的方式有不少，其中網絡擁塞是最多見的一種，也即網絡中部分信道或者部分節點過載而沒法正常工做，對於擁塞致使的拒絕服務攻擊，經常使用的解決策略是判斷出擁塞所在的位置後，利用路由繞過擁塞的部分。

除了拒絕服務攻擊外，還有女巫攻擊 (Sybil Attacks) [21]: Sybil攻擊被定義爲「非法採起多重身份的惡意盜竊行爲」。它最初被描述爲可以擊敗對等網絡中分佈式數據存儲系統冗餘機制的攻擊。除了戰勝分佈式數據存儲系統以外，Sybil攻擊還能夠有效地對抗路由算法，數據聚合，投票，公平資源分配以及阻止不當行爲檢測。發現女巫攻擊的方法有兩種，第一種是: 在無線電測試中，一個節點爲它的每一個鄰居分配一個不一樣的信道，以便進行通訊。而後節點隨機選擇一個通道並偵聽。若是節點被檢測到通道上的傳輸，則假定在通道上傳輸的節點是物理節點(正常節點)。相似地，若是節點沒有被檢測到在指定通道上的傳輸，則該節點假定分配給該通道的標識不是物理標識(虛假節點)。第二種是: 使用隨機密鑰預分發技術，假設有限數量的鑰匙在一個密匙環,一個節點隨機生成的身份不會擁有足夠的鑰匙承擔多重身份，所以沒法在網絡上交換消息由於無效的身份將沒法進行加密或解密消息，或者說一個節點每生成一個新的身份就給予必定量的懲罰, 惡意節點爲了減小損失而選擇不改變身份。

流量分析攻擊 (Traffic Analysis Attacks): 攻擊者經過分析基站周圍流量狀況來肯定攻擊目標。由於傳感器網絡中存在着一些計算能力比較強的節點，這些節點用來收集周圍傳感器的數據後進行分析和處理，具有這樣能力的節點被稱爲「基站」，通常來講基站的計算能力和防禦能力比較強，攻擊者不太可能可能花費較大成本去攻擊基站，可是攻擊者會選擇攻擊基站周圍的傳感器。首先，攻擊者經過分析傳感器傳輸的數據獲取獲得與基站有關的信息，對於一些離基站比較近的傳感器節點，這些節點因爲與基站通訊比較密切，產生的流量比較大，因此經常成爲被攻擊的目標，一旦攻擊者攻陷這些傳感器後會選擇禁用基站或者篡改數據，使得基站收不到收據或者收到虛假數據。處理這類攻擊的方式有: 僞造假數據包傳輸，並且儘可能保證整個網絡流量的均衡，使得攻擊者沒法經過分析流量來選擇攻擊目標。

節點複製攻擊 (Node Replication Attacks)：攻擊者經過複製現有傳感器節點的節點ID來嘗試向現有傳感器網絡中添加節點。以此方式複製的節點可能嚴重中斷傳感器網絡的性能：數據包可能被破壞，甚至發生錯誤路由。這些破壞可能致使網絡斷開，傳感器讀數錯誤等。若是攻擊者經過複製節點可以得到對整個網絡的物理訪問權限，那麼他能夠將密鑰複製到複製的傳感器，也能夠將複製的節點插入網絡中的戰略點。經過在特定網絡中插入複製節點，攻擊者能夠輕鬆操縱網絡的特定部分，並且還有可能使傳感器網絡徹底斷開。

隱私攻擊[22-23]: 傳感器能夠收集目標區域的信息，但是一旦傳感器被攻陷，這些敏感信息就會被泄露，會致使隱私泄露問題。

物理攻擊: 傳感器網絡一般在惡劣的室外環境中運行。在這樣的環境中，傳感器的小形狀因子以及部署的無分散和分佈式特性使得它們很是容易受到物理攻擊，即因爲物理節點破壞而致使的威脅。物理攻擊永久破壞傳感器，因此損失是不可逆轉的。例如，攻擊者能夠提取加密祕密，篡改相關電路，修改傳感器中的程序，或者在攻擊者控制下用惡意傳感器代替它們。

不幸的是，無線傳感器網絡沒法承擔實施許多典型防護策略所需的計算開銷。

安全的廣播和多播

無線傳感器網絡的主要通訊模式是廣播 (broadcasting) 和多播 (multicasting)，例如1對N，N對1和M對N方式，而不是採用傳統互聯網的點對點方式通訊。

將來須要解決的問題

傳感器相關研究須要在如下幾方面進行拓展[1]:

1. Protocols and algorithms for WSNs with heterogeneous sensor nodes. Currently, many WSN protocols/algorithms are based on homogeneous sensor networks. However, sensors with different power capacities, sensing and transmitting range, and computing/processing abilities are usually more practical for constructing highly reliable networks.
2. Security issues. Most existing WSN communication protocols have not addressed security and are susceptible to attacks by adversaries. The issue of integrating security at the design stage in a resources-constrained WSN is a serious technical challenge.
3. Analytical modeling. More accurate and expeditious implementation of WSNs in the real world is highly dependent on the ability to devise analytical models to evaluate and predict WSNs' performance characteristics, such as efficiency for information gathering, delay properties, granularity, and energy consumption. However, due to the diverse forms of applications and massive number of nodes in a single network, many technical problems remain to be solved in modeling the behavior of WSNs.
4. Other issues. Optimal sensor node selection and allocation, discovery, localization, and network diagnoses are other open issues in this direction. Many software issues remain open as well. These include the design of distributed control and coordination algorithms to ensure balanced load assignment and energy consumption; efficient techniques for sensor data storage; and protocols with mobility consideration and dynamic group communications.

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