what is Preferential Attachment (PA) ?

PREFERENTIAL  ATTACHMENT

Wildlife monitoring is an enormous organizational challenge due to the required time and effort for setting and maintaining it. It is particularly difficult when the observed species has a complex social hierarchy and different roles for the members in the social group.

In this paper, we introduce an approach to model a primate social network. The primates have complex social behaviors and network structure. As a result, there is a need for realistic computational models to fully understand and analyze the social behavior of such animal groups. We propose a novel spatial cut-off preferential attachment model with a center of mass concept to model the characteristics of the primate groups and a role determination algorithm, which groups the primates into their roles in the society based on the data collected by the wireless sensor and actor networks (WSAN).

                                                            

 The performance of the monitoring and role determination algorithms, the applicability of the network formation and the mobility models are evaluated through extensive simulations. 

           

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What is Xgraph?

 XGRAPH  

XGRAPH is a general purpose x-y data plotter with interactive buttons for panning, zooming, printing, and selecting display options. It will plot data from any number of files on the same graph and can handle unlimited data-set sizes and any number of data files.

XGRAPH produces wysiwyg PostScript, PDF, PPTX, and ODP output for printing hard-copies, storing, and/or sharing plotted results, and for importing, graphs directly into word-processors for creating documentation, reports, and view-graphs.

XGRAPH includes the ability to specify plotting colors for multi-color plots, as well as line-thickness. It has the ability to use any column of a multi-column file as ordinate and abscissa axis. It also supports automatic resizing of its window. Zoom interactively into any region of a graph by simply dragging a box around the region with your mouse.

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How to make surface coverage in wireless sensor network?

SURFACE COVERAGE

Coverage is a fundamental problem in Wireless Sensor Networks (WSNs). Existing studies on this topic focus on 2D ideal plane coverage and 3D full space coverage. The 3D surface of a targeted Field of Interest is complex in many real world applications. In surface coverage, the targeted Field of Interest is a complex surface in 3D space and sensors can be deployed only on the surface. We show that existing 2D plane coverage is merely a special case of surface coverage. Simulations point out that existing sensor deployment schemes for a 2D plane cannot be directly applied to surface coverage cases.

Sensor networks consist of autonomous nodes with limited battery and of base stations with theoretical infinite energy. Nodes can be sleep to extend the lifespan of the network without compromising neither area coverage nor network connectivity. The area coverage problem with equal sensing and communicating radii. The goal is to minimize the number of active sensors involved in coverage task, while computing a connected set able to report to monitoring stations. Our solution is fully localized, and each sensor is able to make decision on whether to sleep or to be active based on two messages sent by each sensor.

The first message is a “hello” message to gather position of all neighboring nodes. Then each node computes its own relay area dominating set, by taking the furthest neighbor as the first node, and then adding neighbors farthest to the isobar center of already selected neighbors, until the area covered by neighbors is fully covered. The second message broadcasts this relay set to neighbors. Each node decides to be active if it has highest priority among its neighbors or is a relay node for its neighbor with the highest priority.

A wireless sensor network (WSN) is a "smart" system, which consists of numerous small, low-powered, self organizing sensor nodes that have communication and computation capabilities. The sensor nodes of networks can be used to complete tasks assigned according to the application environment in applications related to the military, environmental monitoring, health care, and so on. However, the computation power and communication capacity of sensor nodes within the network are often limited by the environment. 

The sensor network always has some special characteristics such as the dense distribution of sensor nodes, frequently changing topology, multi hop communication mode, and so on. To manage the sensor network more effectively and ensure a better quality of network service, we should consider the coverage issue of networks, which refers to the method of deployment of nodes to achieve better detection. Coverage reflects networks "perceived quality of service" and provides a more reliable guarantee to monitor and control the sensor networks.

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How to identify light weight sybil attack in MANET?

SYBIL ATTACK

The Sybil attack in computer security is an attack wherein a reputation system is subverted by forging identities in peer-to-peer networks. It is named after the subject of the book Sybil, a case study of a woman diagnosed with dissociative identity disorder.

Most networks, like a peer-to-peer network, rely on assumptions of identity, where each computer represents one identity. A Sybil attack happens when an insecure computer is hijacked to claim multiple identities. Problems arise when a reputation system (such as a file-sharing reputation on a torrent network) is tricked into thinking that an attacking computer has a disproportionally large influence. Similarly, an attacker with many identities can use them to act maliciously, by either stealing information or disrupting communication. It is important to recognize a Sybil attack and note its danger in order to protect yourself from being a target.

Large-scale peer-to-peer systems face security threats from faulty or hostile remote computing elements. To resist these threats, many such systems employ redundancy. However, if a single faulty entity can present multiple identities, it can control a substantial fraction of the system, thereby undermining this redundancy. One approach to preventing these “Sybil attacks” is to have a trusted agency certify identities.

Nodes that passively monitor traffic in the network can detect a Sybil attacker that uses a number of network identities simultaneously. We show through simulation that this detection can be done by a single node, or that multiple trusted nodes can join to improve the accuracy of detection. We then show that although the detection mechanism will falsely identify groups of nodes travelling together as a Sybil attacker, we can extend the protocol to monitor collisions at the MAC level to differentiate between a single attacker spoofing many addresses and a group of nodes travelling in close proximity.

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What is file sharing system?

FILE SHARING

Reduction of overhead is essential in increasing the scalability and power efficiency of peer-to-peer (P2P) file sharing systems for mobile ad hoc networks (MANET). Previously researchers mainly focused on reducing overhead of query process, and paid little attention to file transfer process. A cluster-based P2P file sharing protocol for MANET, focusing on file transfer process. This protocol uses the concept of cluster to reduce overhead and applies a three-way handshaking process to form a cluster. Within a cluster, a request agent transmits requests on behalf of other nodes in the cluster, and a provider provides data packets for the cluster at the request of the request agent. By confining the request response process between the request agent and the provider, protocol overhead can be effectively decreased. Moreover, this protocol utilizes request suppression to effectively reduce the number of requests.

The cluster-based P2P file sharing protocol operates alternately in two stages, i.e., cluster formation stage and data transmission stage. During cluster formation stage, a cluster is formed through a three-way handshaking process. After a cluster is formed, the protocol shifts to data transmission stage, during which the provider of the cluster periodically sends data packets to the whole cluster at the request of the request agent. This stage lasts until the provider has provided all requested data blocks, or the cluster breaks up due to node mobility.

 To simplify the design of the protocol, we assume that each node has the same wireless transmission range and will cooperate with other nodes by responding their requests. We also assume that the maximum transmission unit of wireless network is equal for all nodes. The file to be shared is split into blocks of equal size, each of which can fit into a single packet. Each block is assigned a block identifier, which ranges from zero to n-1, where n stands for the number of blocks in the file.

It utilizes the location and interest feature of peers to improve the efficiency of file query. Peers are clustered based on the location and sub clustered based on the interest and file replication in peers so that content delivery can be done fast and overloading on a single peer can be avoided. Current peer-to-peer (P2P) file sharing methods in mobile ad hoc networks (MANETs) can be classified into three groups: flooding-based, advertisement-based, and social contact-based.

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What is secure allocation?

SECURE ALLOCATION

Security for dynamic address allocation service in mobile adhoc networks is still an open issue. A security framework to thwart all possible attacks related to the buddy system based distributed dynamic address assignment protocol (ddaap). The authors' proposed protocol called sheap (secured threshold based ddaap) is based on a fully distributed pki and a threshold based certified pool address allocation model. ns2 simulation results show that, while sheap is deployed, the increasing in communication overhead and latency is quite reasonable. the availability and the security are so guaranteed for the manet auto-configuration service while still ensuring efficiently both network and security parameters for a newly arrived node.

Wireless security is the prevention of unauthorized access or damage to computers using wireless networks. A wireless interactive security system is much simpler to install than a traditional wired system. Wireless security enhance security of different layer and components of mobile networks, mobile ad hoc networks, wireless sensor networks, wireless LAN, Wi-Fi and Wi-Max. A security extension to the OLSR routing protocol developed by SINTEF ICT tailored for use by first responders in emergency and rescue scenarios. We implement the protocol in the NS-2 simulation environment in order to verify correctness and measure the effect on key performance metrics.

A Mobile Ad hoc Network (MANET) is a collection of communication devices or nodes that wish to communicate without any fixed infrastructure and pre-configured organization of available links. The nodes in a MANET are responsible for dynamically discovering other nodes to communicate. Although an ongoing trend is to adopt ad hoc networks for commercial uses, there are still concerns with respect to their vulnerability to security attacks. A number of challenges like open peer-to-peer network architecture, stringent resource constraints, shared wireless medium, dynamic network topology etc. are present in a MANET. The collaborative nature of ad-hoc networks and the necessity of each node to act both as an end system and to perform routing functions makes routing protocols the main target of security attacks.

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What is Shortest path?

SHORTEST PATH

        An algorithm that is designed essentially to find a path of minimum length between two specified vertices of a connected weighted graph

·         Initialize the array smallest Weight so that smallest Weight[u] = weights[vertex, u].

·         Set smallest Weight[vertex] = 0.

·         Find the vertex, v, that is closest to vertex for which the shortest path has not been determined.

·         Mark v as the (next) vertex for which the smallest weight is found.

·         For each vertex w in G, such that the shortest path from vertex to w has not been determined and an edge (v, w) exists, if the weight of the path to w via v is smaller than its current weight, update the weight of w to the weight of v + the weight of the edge (v, w).

NS2 CODE FOR SHORTEST PATH ROUTING

DIJIKSTRA’S ROUTING ALGORITHM

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int main() { Node N0(0); Node N1(1); Node N2(2); Node N3(3); Node N4(4); RoutingVec_t NextHop; RoutingVec_t Parent;  N0.AddAdj(1, 10);  N0.AddAdj(2, 5);  N1.AddAdj(3, 1);  N1.AddAdj(2, 2);  N2.AddAdj(4, 2);  N2.AddAdj(1, 3);  N2.AddAdj(3, 9);  N3.AddAdj(4, 4);  N4.AddAdj(0, 7);  N4.AddAdj(3, 6);  Nodes.push_back(&N0);  Nodes.push_back(&N1);  Nodes.push_back(&N2);  Nodes.push_back(&N3);  Nodes.push_back(&N4);  for (nodeid_t i = 0; i < Nodes.size(); i++)    { // Get shortest path for each root node      printf("\nFrom root %ld\n", i);      Dijkstra(Nodes, i, NextHop, Parent);      PrintParents(Parent);      for (unsigned int k = 0; k < Nodes.size(); k++)        printf("Next hop for node %d is %ld\n", k, NextHop[k]);      printf("Printing paths\n");      for (nodeid_t j = 0; j < Nodes.size(); j++)        {          PrintRoute(i, j, Parent);        }    }  return(0); }

Different ways to identify shortest path routing in ns2

• Transmission and propagation delays.
• Queuing delays.
• Minimum number of hops.

The optimal path is obtained through three steps, which is reverse route calculation in route request (RREQ), reverse route calculation in route reply (RREP) and reverse route calculation in route error (RERR). Experiments have been carried out using network simulator (NS2) and the obtained results are performed better than reactive routing protocol (AODV).

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What is Malicious node?

MALICIOUS NODE

Intrusion Detection Systems (IDS) in Mobile Ad hoc Networks (MANETs) are required to develop a strong security scheme it is therefore necessary to understand how malicious nodes can attack the MANETs. Focusing on the Optimized Link State Routing (OLSR) protocol, an IDS mechanism to accurately detect and isolate misbehavior node(s) in OLSR protocol based on End-to-End (E2E) communication between the source and the destination is proposed. The collaboration of a group of neighbor nodes is used to make accurate decisions. Creating and broadcasting attackers list to neighbor nodes enables other node to isolate misbehavior nodes by eliminating them from the routing table. Eliminating misbehavior node allows the source to select another trusted path to its destination.

ROUTING PROTOCOLS 

                         The routing protocols implemented in MANETs are globally classified into two categories: proactive or table driven protocols and reactive or on-demand protocols. Table driven protocols rely on a table, which maintains consistent up-to-date information concerning routes to all possible destinations, whereas on-demand routing protocols implement source-initiated route organization, where a route is created when desired by the node.

ATTACKS USING MODIFICATION

                           Modification is a type of attack when an authorized party not only gains access to but tampers with an asset. For example a malicious node can redirect the network traffic and conduct DOS attacks by modifying message fields or by forwarding routing message with false values.

ATTACKS USING IMPERSONATION

                         As there is no authentication of data packets in current ad-hoc network, a malicious node can launch many attacks in a network by masquerading as another node i.e. spoofing. Spoofing is occurred when a malicious node misrepresents its identity in the network (such as altering its MAC or IP address in outgoing packets) and alters the target of the networktopology that a benign node can either.

ATTACKS THROUGH FABRICATION

                        Fabrication is an attack in which an authorizedparty not only gains the access but also inserts counterfeit objects into the system. In MANET, fabrication is used to refer the attacks performed by generating false routing messages Gray hole attack We now describe the grayhole attack on MANETS. 

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What are the Difference Between Algorithm and Heuristic?

DIFFERENCE BETWEEN ALGORITHM AND HEURISTIC

An algorithm is a set of well-defined instructions for carrying out a particular task. It must be sound and complete. That mean it must gives you the correct answer and it must works for all cases.Usually, an algorithm is predictable, deterministic, and not subject to chance. An algorithm tells you how to go from point A to point B with no detours, no side trips to points D, E, and F, and no stopping to smell the roses or have a cup of joe.

A heuristic is a technique that helps you look for an answer. Its results are subject to chance because a heuristic tells you only how to look, not what to find. It doesn’t tell you how to get directly from point A to point B; it might not even know where point A and point B are. In effect, a heuristic is an algorithm in a clown suit. It’s less predictable, it’s more fun, and it comes without a 30-day, money-back guarantee.

  

Here is an algorithm for driving to someone’s house: Take Highway 167 south to Puyallup. Take the South Hill Mall exit and drive 4.5 miles up the hill. Turn right at the light by the grocery store, and then take the first left. Turn into the driveway of the large tan house on the left, at 714 North Cedar.

Here’s a heuristic for getting to someone’s house: Find the last letter we mailed you. Drive to the town in the return address. When you get to town, ask someone where our house is. Everyone knows us—someone will be glad to help you. If you can’t find anyone, call us from a public phone, and we’ll come get you.

The difference between an algorithm and a heuristic is subtle, and the two terms overlap somewhat. The main difference between the two is the level of indirection from the solution. An algorithm gives you the instructions directly. A heuristic tells you how to discover the instructions for yourself, or at least where to look for them.

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How to calculate the Throughput Level in NS2?

THROUGHPUT

Following awk file will calculate the throughput with running time (throughput versus time).

The following code will count all the received application packets 

in a network such that we can calculated the network throughput. 

 If  a throughput of a specific node has to be calculated, then we can simply add the node_id in the if condition.

The code simply prints the observed throughput during the time_interval through out the simulation time. We can change the time_interval variable according to our requirements.

In the following code:

·         packet_size * recv * 8.0 gives the total number of bits received. Packet size is the size of packet used in Application layer.

·         diving the value by 1000 gives us the throughput in kbps.

#============== throughput.awk ================

BEGIN {
recv=0;
gotime = 1;
time = 0;
packet_size = 50;
time_interval=2;
}
#body
{
        event = $1
             time = $2
             node_id = $3
             level = $4
             pktType = $7

 if(time>gotime) {

  print gotime, (packet_size * recv * 8.0)/1000; #packet size * ... gives results in kbps
  gotime+= time_interval;
  recv=0;
  }

#========Calculate throughput==========

if (( event == "r") && ( pktType == "cbr" ) && ( level=="AGT" ))
{
 recv++;
}

} #body


END {
;
}

                                        

And finally the throughput level has to be calculated and the above graph diagram illustrates the output of the throughput calculation.

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