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Wireless Sensor Network: Security Vulnerabilities Challenges, Design Principles And Performance Comparison Of Two On-Demand Routing Protocols For Ad Hoc Networks.
Priyanka Manhas1 (Student) Department of Computer Science & Engineering. Chandigarh University (Gharuan, Mohali) India priyankamanhas36@gmail.com
Parminder Kaur2(Asstt. Prof.) Department of Computer Science & Engineering. Chandigarh University (Gharuan, Mohali) India parminder.cu@gmail.com
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from attack. The security issues in MANETs are more challenging than those in traditional wired computer
n today’s competitive industry marketplace, the
companies face growing demands to improve process efficiencies, comply with environmental regulations, and meet corporate financial objectives. Given the increasing age of many industrial systems and the dynamic industrial manufacturing market, intelligent and low-cost industrial automation systems are required to improve the productivity and efficiency of such systems [6], [28]. Traditionally, industrial automation systems are realized through wired communications. However, the wired automation systems require expensive communication cables to be installed and regularly maintained, and thus, they are not widely implemented in industrial plants because of their high cost [29]. Therefore, there is an urgent need for cost-effective wireless automation systems that enable significant savings and reduce air-pollutant emissions by optimizing the management of industrial systems. One of the key issues rising from switching to wireless communication lies in security; while an air gap is among the most effective security measures in wired networks, wireless communication is not as easy to isolate
networks and the Internet. Providing security in sensor
networks is even more difficult than in MANETs due to the resource limitations of sensor nodes and security concerns remain a serious impediment to widespread adoption of these WSNs [27]. An ad hoc network, mobile nodes communicate with each other using multihop wireless links. There is no stationary infrastructure; for instance, there are no base stations. A mobile ad hoc networking (MANET) working group [2] has also been formed within the Internet Engineering Task Force (IETF) to develop a routing framework for IP-based protocols in ad hoc networks. Our goal is to carry out a systematic performance study of two dynamic routing protocols for ad hoc networks: the Dynamic Source Routing protocol (DSR) [3, 4] and the Ad Hoc On-Demand Distance Vector protocol (AODV) [5, 6].
DSR and AODV share an interesting common characteristic they both initiate routing activities on an on demand basis. This reactive nature of these protocols is a significant departure from more traditional proactive
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protocols, which find routes between all source-destination pairs regardless of the use or need for such routes. The key
motivation behind the design of on-Demand protocols is the reduction of the routing load. High routing load usually has a significant performance impact in low-bandwidth wireless links. While DSR and AODV share the on-demand behavior [7] in that they initiate routing activities only in the presence ofdata packets in need of a route, many of their routing mechanics are very different. In particular, DSR uses source routing, whereas AODV uses a table- driven routing framework and destination sequence numbers. DSR does not rely on any timer based activities, while AODV does to a certain extent. One of our goals in this study is to extract the relative merits of these mechanisms. The motivation is that a better understanding of the relative merits will serve as a cornerstone for development of more effective routing protocols for mobile ad hoc networks.
of other nodes in the network that may have the failed link in one of the cached source routes.
3. Promiscuous listening: When a node overhears a packet not addressed to itself, it checks whether the packet could be routed via itself to gain a shorter route. If so, the node sends a gratuitous RREP to the source of the route with this new, better route. Aside from this, promiscuous listening helps a node to learn different routes without directly participating in the routing process.
AODV [5, 6] shares DSR’s on-demand characteristics in that it also discovers routes on an as needed basis via a similar route discovery process. However, AODV adopts a very different mechanism to maintain routing information. It uses traditional routing tables, one entry per destination. AODV uses sequence numbers
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corresponding design directions, respectively. Finally, this
paper is concluded in Section 4.
The key distinguishing feature of DSR [3, 4] is the use of source routing. That is, the sender knows the complete hop-by-hop route to the destination. These routes are stored in a route cache. The data packets carry the source route in the packet header. When a node in the ad hoc network attempts to send a data packet to a destination for which it does not already know the route, it uses a route discovery process to dynamically determine such a route. DSR makes very aggressive use of source routing and route caching. No special mechanism to detect routing loops is needed. Several additional optimizations have been proposed and have been evaluated
to be very effective by the authors of the protocol [7], as
described in the following:
1. Salvaging: An intermediate node can use an alternate route from its own cache when a data packet meets a failed link on its source route.
2. Gratuitous Route Repair: A source node receiving an RERR packet piggybacks the RERR in the following RREQ. This helps clean up the caches
maintained at each destination to determine freshness of
routing information and to prevent routing loops [5]. These sequence numbers are carried by all routing packets. An important feature of AODV is the maintenance of timer- based states in each node, regarding utilization of individual routing table entries. A routing table entry is expired if not used recently. A set of predecessor nodes is maintained for each routing table entry, indicating the set of neighboring nodes which use that entry to route data packets. The recent specification of AODV [6] includes an optimization technique to control the RREQ flood in the route discovery process. It uses an expanding ring search initially to discover routes to an unknown destination. In the expanding ring search, increasingly larger neighborhoods are searched to find the destination.
While WSNs come from wireless and ad-hoc
networks. Some of the sensor network application require wireless and ad-hoc techniques. Although many algorithms and protocols have been proposed for traditional wireless ad-hoc network and they are not well suited for unique feature and application of sensor networks. Important distinction exist between ad-hoc networks and sensor networks greatly effect the system designs including security designs. The difference are as the following:
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3. Production cost: As sensor network consist of large no. of sensor nodes. The cost of a single node is very important to justify the overall cost of the
network. If the cost of the network is more
Sensor network design in influenced by many factors
which include: fault tolerance , scalability, production cost, hardware constraint. Sensor networks may consist of many different type of sensors, such as seismic, low sampling rate magnetic, thermal, visual, infrared, acoustic and radar, which can monitor temperature, humidity, vehicular movement, lighting condition, pressure, soil makeup, noise levels etc.
1. Fault tolerance: Some sensor nodes may fail or be blocked due to lack of power, have physical damage or environmental interference. The failure of sensor nodes should not affect the overall task of the sensor network. This is reliability of fault tolerance issue. The protocols and algorithms may designed to address the level of fault tolerance required by the sensor networks.
2. Scalabilty: Number of sensor nodes deployed in studying a phenomenon may be in the order of
hundreds or thousands. The new scheme is able to work with this no. of nodes. They must also utilize the high density nature of the sensor networks. The number of nodes in a region can be used to indicate the node density. The node density depend upon the application in which the sensor nodes are deployed.
4. expensive than deploying traditional sensors, then the sensor network is not cost justified. As a result the cost of a sensor node has to be kept low.
5. Hardware constraints: Sensor node comprising
of four main omponents: Sensing Unit, Processing
Unit, Transceiver Unit And Power Unit.
Where sensing units are composed of two subunits: sensors or ADCs(Analog to digital converters). The analog signals produced by the sensors based on the observed phenomenon are converted to digital signals by the ADC, and then fed in to the processing units.
Processing unit which is generally associated with a small storage unit, manages the procedures that make the sensor node collaborate with the other nodes to carry out the assigned sensing tasks.
A transceiver unit connects the node to the network. The transceiver unit of sensor nodes may be a passive or active optical devices in smart dust motor a radio frequency device(RF)
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The most important component of the sensor node is power unit. Power units may be supported by a power
scavenging units such as solar cells.
They may also have application dependent additional components such as location finding system, power generater and a mobilizer.
1. Resource Constraints: The design and implementation of IWSNs are constrained by three types of resources: a) energy; b) memory; and c) processing. Constrained by the limited physical size, sensor nodes have limited battery energy supply [6]. At the same time, their memories are limited and have restricted computational capabilities.
2. Dynamic Topologies And Harsh
environments, the topology and connectivity of the
network may vary due to link and sensor-node failures. Furthermore, sensors may also be subject to RF interference, highly caustic or corrosive
and high bit error rates are observed in communication. In addition, wireless links exhibit
widely varying characteristics over time and space due to obstructions and noisy environment. Thus, capacity and delay attainable at each link are location-dependent and vary continuously, making QoS provisioning a challenging task.
6. Security: Security should be an essential feature in the design of IWSNs to make the communication safe from external denial-of- service (DoS) attacks and intrusion. IWSNs have special characteristics that enable new ways of security attacks. Passive attacks are carried out by eavesdropping on transmissions including traffic analysis or disclosure of message contents. Active attacks consist of modification, fabrication, and interruption, which in IWSN cases may include node capturing, routing attacks, or flooding.
7. Large-Scale Deployment And Ad Hoc
number of sensor nodes (hundreds to thousands or
even more), which might be spread randomly over
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environments, high humidity levels, vibrations,
dirt and dust, or other conditions that challenge
performance [28]. These harsh environmental conditions and dynamic network topologies may cause a portion of industrial sensor nodes to malfunction [7].
3. Quality-Of-Service (Qos) Requirements: The wide variety of applications envisaged on IWSNs
will have different QoS requirements and specifications. The QoS provided by IWSNs refers to the accuracy between the data reported to the sink node (the control center) and what is actually occurring in the industrial environment. In addition, since sensor data are typically time- sensitive, e.g., alarm notifications for the industrial facilities, it is important to receive the data at the sink in a timely manner. Data with long latency due to processing or communication may be outdated and lead to wrong decisions in the monitoring system.
4. Data Redundancy: Because of the high density
in the network topology, sensor observations are
highly correlated in the space domain. In addition, the nature of the physical phenomenon constitutes the temporal correlation between each consecutive observation of the sensor node.
5. Packet Errors And Variable-Link Capacity:
Compared to wired networks, in IWSNs, the
attainable capacity of each wireless link depends
on the interference level perceived at the receiver,
the deployment field. Moreover, the lack of
predetermined network infrastructure necessitates
the IWSNs to establish connections and maintain network connectivity autonomously.
8. Integration With Internet And Other
commercial development of IWSNs to provide
services that allow the querying of the network to retrieve useful information from anywhere and at any time. For this reason, the IWSNs should be remotely accessible from the Internet and, hence, need to be integrated with the Internet Protocol (IP) architecture. The current sensor-network platforms use gateways for integration between IWSNs and the Internet [2]. Note that although today’s sensor networks use gateways for integration between IWSNs and the Internet, the sensor nodes may have IP connectivity in the future [18].
To deal with the technical challenges and meet the diverse IWSN application requirements, the following design goals need to be followed. Though there are varieties of challenges in sensor networks, here we focus on different security issues and possible remedies of those. Though security is a very important issue in WSN, due to various resource limitations and the salient features of a
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WSN, the security design for such networks is significantly challenging.
1. Low-Cost And Small Sensor Nodes: Compact and low cost sensor devices are essential to accomplish large scale deployments of IWSNs. Note that the system owner should consider the cost of ownership (packaging requirements, modifications, maintainability, etc.), implementation costs, replacement and logistics costs, and training and servicing costs as well as the per unit costs all together [9].
2. Scalable Architectures And Efficient
industrial applications with different requirements. It is necessary to develop flexible and scalable architectures that can accommodate the requirements of all these applications in the same infrastructure. Modular and hierarchical systems can enhance the system flexibility, robustness, and reliability. In addition, interoperability with
existing legacy solutions, such as fieldbus- and
organizing architectures and protocols. Note that, with the use of self-configurable IWSNs, new
sensor nodes can be added to replace failed sensor nodes in the deployment field, and existing nodes can also be removed from the system without affecting the general objective of the application.
7. Fault Tolerance And Reliability: In IWSNs, based on the application requirements, the sensed
data should be reliably transferred to the sink node. Similarly, the programming/retasking data for sensor operation, command, and queries should be reliably delivered to the target sensor nodes to assure the proper functioning of the IWSN. However, for many IWSN applications, the sensed data are exchanged over time-varying and error prone wireless medium. Thus, data verification and correction on each communication layer and self-recovery procedures are extremely critical to provide accurate results to the end-user.
8. Resource-Efficient Design: In IWSNs, energy efficiency is important to maximize the network
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Ethernet-based systems, is required.
3. Secure Design: When designing the security
mechanisms for IWSNs, both low-level (key establishment and trust control, secrecy and authentication, privacy, robustness to communication DoS, secure routing, resilience to node capture) and high-level (secure group management, intrusion detection, secure data aggregation) security primitives should be ddressed [20]. In addition, because of resource limitations in IWSNs, the overhead associated with security protocols should be balanced against other QoS performance requirements.
4. Data Fusion And Localized Processing:
Instead of sending the raw data to the sink node
directly, sensor nodes can locally filter the sensed
data based on the application requirements and
transmit only the processed data, i.e., in network processing. Thus, only necessary information is transported to the end-user and communication overhead can be significantly reduced.
5. Application-Specific Design: In IWSNs, there
exists no one-size-fits-all solution; instead, the alternative designs and techniques should be developed based on the application-specific QoS requirements and constraints.
6. Self-Configuration And Self-Organization: In
IWSNs, the dynamic topologies caused by node failure/mobility/ temporary power-down and large-scale node deployments necessitate self-
lifetime while providing the QoS required by the
application. Energy saving can be accomplished in every component of the network by integrating network functionalities with energy efficient protocols, e.g., energy-aware routing on network layer, energy-saving mode on MAC layer, etc.
9. Time Synchronization: In IWSNs, large numbers of sensor nodes need to collaborate to perform the sensing task, and the collected data are usually delay-sensitive [2], [9]. Thus, time synchronization is one of the key design goals for communication protocol design to meet the deadlines of the application. However, due to resource and size limitations and lack of a fixed infrastructure, as well as the dynamic topologies in IWSNs, existing time synchronization strategies designed for other traditional wired and wireless networks may not be appropriate for IWSNs. Adaptive and scalable time-synchronization protocols are required for IWSNs.
The IWSNs have the potential to improve productivity of industrial systems by providing greater awareness, control, and integration of business processes. Despite of the great progress on development of IWSNs, quite a few issues still need to be explored in the future. For example, an efficient deployment of IWSNs in the real world is highly dependent on the ability to devise analytical models
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to evaluate and predict IWSNs performance characteristics, such as communication latency and reliability and energy efficiency. However, because of the diverse industrial- application requirements and large scale of the network, several technical problems still remain to be solved in analytical IWSN models. We have compared the performance of DSR and AODV, two prominent on- demand routing protocols for ad hoc networks. DSR and AODV both use on-demand route discovery, but with different routing mechanics. In particular, DSR uses source routing and route caches, and does not depend on any periodic or timer-based activities. DSR exploits caching aggressively and maintains multiple routes per destination. AODV, on the other hand, uses routing tables, one route per destination, and destination sequence numbers, a mechanism to prevent loops and to determine freshness of routes. The general observation from the simulation is that for application-oriented metrics such as delay and throughput, DSR outperforms AODV in less “stressful” situations (i.e., smaller number of nodes and lower load and/or mobility). We believe that mechanisms to expire routes and/or determine freshness of routes in the route
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cache will benefit DSR’s performance significantly. We
believe that mechanisms to expire routes and/or determine
freshness of routes in the route cache will benefit DSR’s performance significantly. Since AODV keeps track of actively used routes, multiple actively used destinations also can be searched using a single route discovery flood to control routing load. In general, it was observed that both protocols could benefit:
1. From using congestion-related metrics (e.g., queue
lengths) to evaluate routes instead of emphasizing
the hop-wise shortest routes.
2. By removing “aged” packets from the network.
The aged packets are typically not important for the upper layer protocol, because they will probably be retransmitted.
These stale packets do contribute unnecessarily to the load in the routing layer. Other open issues
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