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Sensor Networks

by: Buck Ankunding

Sensor Networks CMPE 259

Buck Ankunding
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This 8 page Class Notes was uploaded by Buck Ankunding on Monday September 7, 2015. The Class Notes belongs to CMPE 259 at University of California - Santa Cruz taught by Staff in Fall. Since its upload, it has received 47 views. For similar materials see /class/182224/cmpe-259-university-of-california-santa-cruz in Computer Engineering at University of California - Santa Cruz.

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Date Created: 09/07/15
ReInForM Reliable Information Forwarding using Multiple Paths in Sensor Networks Budhaditya Deb Sudeept Bhatnagar and Badri Nath Dataman Lab Dept of Computer Science Rutgers University Piscataway NJ USA bdebsbhatnagbadricsrutgersedu Abstract Sensor networks are meant for sensing and disseminating information about the environment they sense The criticality of a determines it 39 r A He e data dissemination in a sensor network should be information are Such informationawareness is essential rstly to disseminate critical information more reliably and secondly to consume network resources proportional to criticality of information In this paper We describe a protocol called ReInForM to support information awareness in sensor networks Using ReInForM data can be delivered at desired levels ofreliability at proportional cost in spite ofthe presence of signi cant channel errors It uses the concept of dynamic packet state in context of sensor networks to control the number of paths required for the desired reliability paths We also show that for uniform unit disk graphs multiple edgedisjoint paths numbering as many as the average node degree exist between any source and sink with very high probability These paths exist in a thin band between source and sink having low deviation from the optimalpath ReInForm 39 39 39 I I in 39 39 IurWardin mechani m wniuue uh inuse of all possible paths in this band Thus as a side effect ReInForM leads to load balancing as Well I INTRODUCTION A sensor network is comprised of small devices or sensor nodes with computation communication and sensing capabilities l 2 3 4 Since sensor nodes are highly resource constrained all applications and protocols consume minimal network resources Hence research in sensor networks focused on energy ef ciency while providing basic networking and information dissemination functionality 5 4 However the main purpose of a sensor network is to disseminate information about the environment it senses and hence the data dissemination process should be informationaware Consider a case where a temperature sensor in a forest senses 60F on a normal spring day On the other hand another sensor senses a temperature of lOOOF at the same time From a monitor s point of View the packet containing the lOOOF temperature is much more important as it could indicate a forest re and hence should reach the monitoring node with high reliability and low latency Note that reliability in data delivery is an important consideration since sensor networks typically would have high channel errors Since nodes may be deployed at random sometimes in hostile terrain there could be signi cant devialtion in the local channel errors from the global estimate Also if the number of hops from source to sink is high the probability of a packet reaching the sink becomes very low Data centric routing 5 considers the information dissemination aspect of a sensor network by giving more im portance to the data rather than than the source of the data However it doesn t consider the fact that the reliability in data delivery should depend on the information content in data being sent Flooding can be used to deliver packets with high reliability but the overhead incurred is signi cant Using default routing for normal data and ooding for critical data does not provide a graceful transition both in terms of attained reliability and incurred overhead Also this kind of a scheme would overlook the fact that achieved reliability is heavily dependent on prevalent channel error rates Any data dissemination protocol which is not adaptive to channel error rates and does not have a notion of information awareness would either be spending too much resources for unimportant information or would not be delivering really important inform ation with high reliability The above highlight the need for informationawareness in sensor networks and adaptability to channel errors along with differential consumption of network resources based on the criticality of data This paper is intended to solve the above problems Based on the criticality of data inside a packet different priority levels are assigned Each priority levels maps to a desired reliability in data delivery The main concept used in this paper is introduction of redundancy in data delivered to increase probability of data delivery This redundancy is in the form of multiple copies of the same packet which travels to the destination among multiple paths This research Work Was supported in part by DARPA under contract number N6660010018953 and a grant from CISCO systems We propose a moultpath forwarding protocol called RelnForM for providing desired reliability in data delivery based on packet priority It uses only local knowledge of error rates and neighborhood at each node We achieve this by a technique analogous to dynamic packet state 8 9 Packets carry minimal state aiding in forwarding decisions at a node so as to provide desired reliability at the global scale Our algorithm does not require any data caching at any node which is important because sensor nodes have limited memory Use of dynamic packet state and randomized forwarding mechanism leads to use of all nodes in the a between source and sink at random Thus the mechanism as a side effect achieves load balancing effect as well Even for single path forwarding RelnForM is desirable because of its load balancing effect The protocol is supported by our observations on the existence of multiple edgedisjoint paths in connected unit disk graphs of uniform density Our simulations showed that for connected unit disk graphs the number of edge disjoint paths is equal to the average node degree with high probability Moreover very few of these paths have signi cant deviation in the number of hops from the optimal In our simulations the average deviation was less than 2 hops for all cases considered This implies that almost all these disjoint paths exist in a thin band between the source and the sink The paper is organized as follows In section 2 we discuss some of the related work In section 3 we describe the network model and assumptions used in our work In section 4 we discuss our study of multiple paths in random unit disk graphs which supports the idea of multipath approach to providing reliability In section 5 we describe the Re nForm in detail Section 6 gives some simulation results for the performance of our algorithm Finally in section 7 we discuss conclusions and future work H RELATED WORK Support for inform ationawareness in sensor networks can be provided using a framework similar to differentiated services 6 Every data packet is assigned a priority level based on its information content and criticality When a node receives a packet it looks at its priority level and acts accordingly to provide the desired reliability The concept of such a differentiated services and data prioritizing framework for sensor networks was introduced in 7 A multipathmultipacket forwarding protocol was proposed for delivering data packets at required reliability based on data priority By using redundancy in packets the protocol controls the reliability of packet delivery The protocol uses a probabilistic ooding scheme to create multiple paths form source to sink lt adapts to any channel error and topological changes However the main drawback of the algorithm is that it requires periodic update of forwarding parameters to adapt to the changes RelnForM does not require any periodic reinforcements In 12 multiple paths from source to sink is used in diffusion routing framework 5 to quickly recover from path failure The multiple paths provided by such protocols could be used for sending the multiple copies of each packet However it incurs extra overhead of multiple path formation and maintenance of path state in each node and is not adaptive to channel errors Similarly for mobile adhoc networks different multipath extensions to well known routing algorithms have been proposed l3 14 15 16 However the main purpose of these multipath routing schemes is to increase robust ness in paths by quickly recovering from broken paths they are also not adaptive to local channel error rates For streaming video over a Wireless Lan different schemes for prioritized forward error correcting codes have been proposed 18 17 They allow different resolution layers in streaming video to be protected by different channel codes based on their importance Based on the local channel error and packet importance similar approach could be adopted to provide the desired reliability However for sensor networks computationally simpler algorithms have to be designed since nodes have limited computation power and memory This is an area of future work 111 NETWORK MODEL amp TERMINOLOGY In this section we describe the network model that we assume for the underlying sensor network The network graph G V E has V n vertices and m edges The vertices represent the sensor nodes which have uniform random distribution The edges represent the wireless communication links between nodes The links are assumed to be symmetricthe graph is undirected and all nodes have equal communication radius R Thus G is a unit disk graph in which an edge vi 6 E iff listanczawi W S R There is a single monitoring node also called the sink to which each sensor sends its data 1 The sink periodically broadcasts a routing update packet which is ooded throughout the network with each node forwarding it at most IHaving multiple monitoring nodes does not require any changes to our protocol We assume so for the ease of exposition TABLE I THE AVERAGE DEVIATION IN NUMBER OF HOPS FROM OPTIMAL FOR DIFFERENT NUMBER OF NODES mu nudes 2m nudes e auu nudes 21mm diunne edmthe len atlhese mm m 15 an 2m 25 cammummn Ramon Fig 1 Probability of Edge Disjoint Paths equal to node Degree against density once During each routing update a node i becomes aware of its neighbors and the number of hops it is away from the sink 12 Node i also notes down the number of its neighbors which are I i Llu II 1 hops away from the sink We assume a TDMA MAC layer in the network as proposed in l l for collision free transmissions Each node is also assumed to have knowledge of the local channel error which can be obtained over a period of time The number of neighbors of node i which is also its degree in G is represented by if A packet has a priority level l where l 6 l l2 l The number of priority levels it may depend upon the application and the levels of differentiation desired by the user Each priority level l is associated with a reaching probability P ie a packet with priority level l is expected to reach the monitor with probability P IV STUDY OF MULTIPLE PATHS IN RANDOM UNIT DISK GRAPHS ReInForM provides desired reliability in packet delivery in presence of any channel error rate by sending multiple copies of a single packet along multiple paths Hence it relies heavily on the existence of multiple paths from source to sink Only if suf ciently large number of paths exist from source to sink without too much deviation in the number of hops from the optimal the multipath approach would succeed When the number of paths between any two nodes is not suf cient for providing the reliability required there may be more one copy of a packet per path The reliability that can be achieved using multipath forwarding depends on the expected number of such paths The number of edge disjoint paths gives a good bound for the above because number of paths would be at least as large the number of disjoint paths We note that the maximum possible number of disjoint paths between a source and a sink is the minimum of node degrees of source and sink We conducted several experiments to nd relation between the number of edgedisjoint paths between a source and a sink and the miudegrcdsm c alch 39 edgedisjoint paths we used a greedy algorithm which nds the shortest path between source and s1nk and removes all edges from the graph and nds the next shortest path in the current graph and so on Figure 1 shows the results for the case of a unit disk graph of uniform density For a reasonable density the number of disjoint paths between any pair of nodes is equal to the average node degree of the graph with very high probability Thus there is a direct correlation in the average node degree with the number of edgedisjoint paths Also the result indicated that the probability that the number of edge disjoint paths equals the maximum number possible which is limited by the node degree is very high when the network is connected Reference 10 shows through simulation studies that expected neighborhood size for a network to be connected is six Our simulations indicate that for a uniform random unit disk graph a network slightly more dense than a minimal connected graph is 75 Te 8 n 3 g A Singlz Path Farwardmg a Mulnpulh Farwumng Fig 2 Single Path Forwarding vs MultiPath Forwarding suf cient to provide edgedisjoint paths equal to the average node degree Our second experiment studies the expected deviation in hops of these edgedisjoint paths from the optimal path The simulation results shown in table I indicate that for all the topologies and densities considered the average deviation is not more than two hops In fact the maximum deviation for any single pair of node occurs for the nodes which are just 1 hop away from the sink which is expected because the path remaining after removing all but one neighbors of the lasthop node would likely have a path length large relative to the optimal path length These two results signi cantly uphold the idea of multipath forwarding for reliability The fact that the number of edgedisjoint paths from any node to the sink is nearly equal to the node s degree implies that the node has a lower bound on the number of paths at its behest These paths being of nearly equal length means that choosing any path randomly for data delivery does not incur a penalty in terms of latency and at the same time allows us to do load balancing These observations enable a node to take local decisions to determine the number of forwarding paths and the next hop for data forwarding This coupled with corrections for local information form the basis of the ReInForM protocol V REINFORM RELIABLE INFORMATION FORWARDING USING MULTIPLE PATHS In this section we describe the multipath forwarding algorithmReInForM for providing desired reliability in data delivery The main idea is to provide reliability in data delivery by introducing redundancy in the form of multiple copies of each packet delivered through multiple paths from source to sink Based on the local knowledge of some network conditions channel error hops to sink outdegree etc the source decides to send multiple copies of packets through multiple paths Each packet header contains information about network conditions from the previous step which is used for forwarding decisions As a packet travels toward the sink these elds are updated at each node to account for local deviation in network conditions The method is analogous to Dynamic Packet Stale DPS approach used for data networks 8 9 The key idea in DPS is to carry some state information in the packet header enabling the network to serve the packet in a desired manner even though the forwarding nodes do not maintain any packet state While in data networks this technique has been used for providing bandwidth and delay guarantees to ows we use it to provide a lightweight and localized mechanism for reliability in information dissemination The mechanism is useful in sensor networks because it does not require any caching or state maintenance at intermediate nodes which would be required in any acknowledgment based scheme It adapts to any channel errors and topological deviations using only local knowledge while maintaining the desired level of reliability at global scale The overhead incurred is proportional to the desired reliability In sensor networks wireless channel can have signi cant channel error Hence the probability of a packet reaching the sink can be low if the number of hops from source to sink is high In our approach we try to increase this proba bility by introducing redundancy in packets by forwarding copies of packets along multiple paths This approach is depicted in gure 2 Note that while forwarding multiple packets along a single path can also be used to provide a desired reliability it would overuse the default path and create hot spots Moreover the expected latency in such a case would be higher than that of multipath approach where multiple copies of the packet can travel in parallel We now describe the ReInForM protocol and later show its effectiveness A Protocol Description On generating a packet the source node determines the importance of the information it contains and decides the desired reliability T3 for it It also knows the local channel error 3 and its hop distance from sink 1 Using these values the source computes the number of paths or equivalently the number of copies of the packet to be sent P required for delivering the packet at desired reliability to the sink as l lagl nil h 1 gl 1 3 5 The source broadcasts the packet and puts certain DPSdynamic packet state elds in its header The key aspect of our algorithm is the DPS mechanism which allows the receiving nodes to take local decisions about forwarding the packets Before describing the DPS elds we bring forth some issues which need to be addressed using DPS Each receiving node has to ascertain the reliability that the source expects it to provide from itself to sink Since the source s computation was done using its local channel error and its distance from sink the reliability expected of the receiving node should be adjusted accordingly We don t want to cache any packets Each receiving node should take a forwarding decision based on the contents of the packet s DPS elds The direction of ow of each packet should be towards the sink as much as possible While we could initially deviate from the optimal path length once the required number of paths have been created the copies of the packet should have a gradient towards the sink We address these issues in our algorithms as follows The source 5 is at a distance 1 from the sink The neighborhood set of the source is divided into 3 subsets HH0 and Hfquot which contain neighbors at distance 1 l 3 and 12 1 respectively The source selects one of the members of H 3 set at random and designates it the next hop Since the graph is assumed to be connected there is at least one node in set H 3 This ensures that at least one member towards the sink forwards Choosing a random next hop helps in load balancing The source also has to compute the following DPS elds for the packet P P o P These values represent the number of paths that each node in Hf H30 and Hfquot re spectively is required to create le if this value is greater than 1 then each node would forward the packet and more than one of its neighbors would forward 23 The channel error at source This value is used in association with local channel error at a receiving node to make local corrections to DPS elds 13 The hop distance of the source to sink At each step our aim is to create the desired number of paths while maintaining a forwarding bias towards the nodes having lower distance to sinkThus paths for H 3 H 30 H 3 are assigned in order such that rst set is assigned paths rst Only if more paths are left the second set gets assigned and so on Since packets from nodes in H 5de 3 take one and two hops more than H 3 the paths are assigned with the following ratios P r3 231 2 Pmo Pn PM 71 39 l 32 Pmo is assigned only if number ofpaths P exceed number ofnodes in H and PH is assigned only ifnumber of paths exceed number of nodes in H and H 30 The expected number of paths P to be spawned at the source is computed by subtracting l 23 from equation 3 as follows P lagl r3 lagl 1 23 5 This is done to compensate for the default path created by designating one next hop node to forward as described earlier The probability of this packet reaching the default node is l a 3 Based on the expected number of paths P the distribution among the three neighbor sets is done in ratios given by equation 2 If a receiving node is the default next hop it always forwards the packet Other receiving nodes determine whether or not to forward the packet using the following criteria If the path value P associated with it is greater than 1 it always becomes a forwarding node If the value is less than 1 it becomes a forwarding node with a probability equal to the value The nodes which decide not to forward the packet simply drop it The other nodes which decide to forward have to adjust the values of the DPS elds so that they remain consistent with the source s calculations To do this each node i has to update T333II3 to Ti 311 while taking into account the three local Hsets Hf Hi Hfquot Node i computes the required reliability r as 1 33 3 n r 1 r gm 1 4 C D Fig 3 Illustration ofthe Band Based Multipath Forwarding Paths For all four cases the required reliability is 70 The source is in lower left comer and the sink at the upper right corner ofthe graph A shows e pa t en y a single packet for zero channel error and B shows the band for zero channel error for 10 packets C shows the paths taken for a single packet when channel error is 30 and D shows the band for 10 packets when channel error is 30 Effectively the node now becomes a source in its own right Using its local channel error a and its hop distance to sink 12 the node uses the same process to compute the path values for its neighbors and the process continues The algorithm essentially creates a band of parallel paths between source and sink The width of the band and the number of paths depend on the error rates desired reliability and hop distance between source and sink Figure 3A and 3C show paths for a single packet between a pair of source and sink for error rates 0 and 03 respectively and desired reliabilities of 07 on the same topology Figures 303 and 3CD show the bands formed for 10 different packets between same pair of source and sink Lmder the same conditions as earlier Note that the forwarding duty is distributed across the band and is not concentrated on a single path Similarly the band is limited in width which can not be done using ooding VI SIMULATION In this section we show some of the simulation results illustrating features of ReInForM The simulations are done on a Lmiform topology consisting of 300 nodes spread in a square area of lOOmxlOOm The channel error rate is normally distributed across the eld with the mean and deviation varying for different simulations In all simulations the source is located in lower left zone and the sink at the upper right zone as shown in gure The rst simulation shows the reliabilityoverhead control of ReInForM For this simulation the communication Attained Reliabililv 5 m 15 35 w 45 so 2m 25 an Channel Enav 0 Fig 4 Attained Reliability by ooding single path forwarding andmultipath forwarding targeting 40 and 70 reliability for nclreasing channel error 5 Overhead 5 m 15 2m 25 an Channel Enav we Fig5 Overhead incurred by ooding single path forwarding and multipath forwarding targeting 40 and 70 reliability for nclreasing channel error range of all nodes is set to 20m This results in a 7 hop distance between source and sink The source sends 200 packets to the sink The mean channel error is increased from 0 to 50 Figure 4 shows the reliability attained for single hop forwarding ooding and two instances of multipath forwarding at desired reliability of 40 and 70 respectively We see that ooding always provides high reliability close to 100 whereas the reliability provided by single path forwarding is negligible We see that ReInForM provides reliabilities close to their desired reliabilities Figure 5 shows the overhead incurred in terms of number of packets transmitted for each of the above cases The overhead incurred by ooding is very high and that incurred by single path forwarding very low The overhead incurred by the multipath forwarding schemes increases with the error rate but is signi cantly less than that of ooding even for an error rate of 50 This experiment shows that even for small channel errors the reliability provided by single path forwarding is very low Flooding on the other hand incurs a huge overhead even when the channel conditions are good Our multipath forwarding scheme adapts to the network condition and provides desired reliability at a reasonable cost We see that when the expected number of paths required to provide desired reliability is close to the total number of nodes in the network for example with 60 error rate and required reliability of around 80 the expected number of paths is well beyond 300 nodes it is better to ood the network in a controlled manner rather than rely on ReInForM The second simulation shows the impact of increasing desired reliability for a constant channel error For this simulation the communication range of all nodes is 20m and the channel error is xed at 25 Figure 6 shows the attained reliability for ooding single path forwarding and multipath forwarding The corresponding overhead incurred is shown in gure 7 Again the adaptive nature of our algorithm is highlighted visavis the two extreme forwarding methods ooding and single path forwarding Attained Rehahi nv u 5 u 7 DesiredReiath ity for ooding single path forwarding and multipath forwarding for channel error xed at 20 Overhead x mpmas u 5 u 7 Desired Rehabimv Fig 7 Overhead incurred by ooding single path forwarding and multipath forwarding under 20 and 40 channel errors VII DISCUSSION In this paper we argue that mechanisms to support information awareness and service guarantees for information dissemination is essential for sensor networks This is a preliminary investigation into the issue of information awareness in sensor networks The work raises some important issues with respect to information awareness What is Quality of ServiceQoS from the perspective of sensor networks What metrics other than Reliabil ity and Latency in data delivery are relevant for sensor networ In an actual sensor network what network services are realizable ie are the lightweight mechanisms as proposed in this paper light enough Is QoS a stand alone service that a network provides or should it be used in conjunction with other network protocols For example in content aware data dissemination like directed diffusion the sink propagates an interest in network and the nodes satisfying that interest reply back It may be more relevant to have a push based mechanism where data dissemination is triggered based on the information content in the sensed data In this regard a node could use a QoS capable network to provide the sink with important information quickly The sink in turn could generate a corresponding interest message to ask if there are other nodes which sense that important information as well This removes the responsibility of expecting the unexpected from the sink This paper assumes that packets are not cached in sensor nodes because of memory constraints This may lead to multiple transmissions of the same packet at a node It can be shown that overhead could be reduced signi cantly by caching the packets To what degree is caching permissible in sensor networks in practice This work assumes that the nodes can compute the information content and importance of sensed data For example pattern matching or machine learning techniques may be used for this purpose This aspect needs to be investigated further


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