resolution strategy. On the other hand, which data to cache is handled with a cache management strategy, which uses two simple rules to decide which data item to keep in limited cache. They categorize the items as primary and secondary based on their existence in the neighborhood. If a data item is primary, it has priority in cache. If it is secondary, then LRU (Least Recently Used) cache management algorithm is applied to the existing cache.COOP also uses TTL-based consistency control mechanism for cached data items. In cache resolution, when a node receives a data request, first of all it checks its own memory. If data is not in memory, it checks its RRT (Recent Requests Table), this keeps the previously received requests. This table avoids duplicated flooding for the same data item that was previously searched. If still no matching is found, then COOP starts an adaptive flooding, which limits the number of hops that a broadcast packet can travel. Adaptive flooding aims to find a cache of the requested item in the neighborhood. If it cannot find, it directly sends the request to the server (or source of the requested item) using the underlying routing protocol. While the request is carried to the server, if an intermediate node finds the requested item in its cache, it stops forwarding and returns the data to the requester. The performance of COOP is studied using mathematical analysis and simulations from the perspectives of data availability, time efficiency, and energy efficiency. This cooperative caching identify open optimization problem to be addressed for the size of the cooperation zone .The analysis and simulation results show th at COOP significantly reduces response delay and improves data availability with proper settings of the cooperation zone radius. However, the mathematical analysis lacks the use of the metric average number of hops which is essential in predicting the number of hops in the cooperation zone. In the above mentioned techniques none has used the average number of hops to predict the number of hops in the cooperation zone. However, Chand  proposes the analytical model for average number of hops but the work has not been fully implemented.
The simulation studies involve the deterministic small network topology with 5 nodes as shown in Fig.1. The proposed energy efficient algorithm is implemented with MATLAB. We transmitted same size of data packets through source node 1 to destination node 5. Proposed algorithm is compared between two metrics Total Transmission Energy and Maximum Number of Hops on the basis of total number of packets transmitted, network lifetime and energy consumed by each node. We considered the simulation time as a network lifetime and network lifetime is a time when no route is available to transmit the packet. Simulation time is calculated through the CPUTIME function of MATLAB. Our results shows that the metric total transmission energy performs better than the maximum number of hops in terms of network lifetime, energy consumption and total number of packets transmitted through the network.
In this paper, a mechanism is proposed which is helpful in prevention of wormhole attack in ad hoc network is verification of sequence number of sending nodes by receiving node because each legitimate node in the network contains the IP address of every other legitimate nodes of same network. In proposed solution, if sender wants to send the data to destination, firstly it creates a secure path between sender and receiver with the help of sequence number and number of hops. If there is presence of any malicious node in between the path then it is identified because malicious node does not have its own sequence number and also the number of hops is large.
The simulation results showed that the proposed greedy algorithm performs with relay nodes for better transmission for the maximum number of hops metric. The proposed greedy algorithm provides reducing the energy efficient path for data transmission and maximizes the lifetime of entire network. By distributing the sensed data to multiple paths, the energy consumption of each sensor node can be balanced to prolong network lifetime. We can increase the number of nodes and analyze the performance. In the future, the proposed routing algorithm will be extended to sleep mode and therefore a longer network lifetime can be achieved.
Impact of number of wavelengths per optical Fiber Figures 7d, 8a and b plot the variation of blocking ratio, mapping cost and average number of hops against the number of wavelengths used per optical fiber link. First, the blocking ratio is clearly closely related to the number of wavelengths used to transmit service request data among MEC-DC locations. The blocking ratio actually decreases as the number of wavelengths increases. Second, these figures show that, for a given demand pattern, increasing the number of wavelengths beyond a certain value has no impact on mapping cost and the average number of hops. For example, when the number of wavelengths equals 5, the map- ping cost and the average number of hops are quite constant. These results help to optimize capital expendi- tures while honoring the QoS requirements inherent in media cloud demand. Also, the number of hops is cru- cial in an optical network as it might lead to O-E-O conversion. Care needs to be taken to reduce O-E-O conversion as the system strives to increase its link resource use.
DSDV is one of the most well-known table-driven routing algorithms for MANETs. The DSDV routing algorithm is based on the classical Bellman-Ford Routing Algorithm (BFRA) with certain improvement . Every mobile station maintains a routing table with all available destinations along with information like next hop, the number of hops to reach to the destination, sequence number of the destination originated by the destination node, etc. DSDV uses both periodic and triggered routing updates to maintain table consistency. Triggered routing updates are used when network topology changes are detected, so that routing information is propagated as quickly as possible. Routing table updates can be of two types – full dump and incremental. Full dump packets carry all available routing information and may require multiple Network Protocol Data Units (NPDU); „incremental‟ packets carry only information changed since the last full dump and should fit in one NPDU in order to decrease the amount of traffic generated. Mobile nodes cause broken links when they move from place to place. When a link to the next hop is broken, any route through that next hop is immediately assigned infinity metric and an updated sequence number. This is the only situation when any mobile node other than the destination node assigns the sequence number. Sequence numbers assigned by the origination nodes are even numbers, and sequence numbers assigned to indicate infinity metrics are odd numbers. When a node receives infinity metric, and it has an equal or later sequence number with a finite metric, it triggers a route update broadcast, and the route with infinity metric will be quickly replaced by the new route. When a mobile node receives a new route update packet; it compares it to the information already available in the table and the table is updated based on the following criteria:
Fig. 11 shows the Video Frame Delivery Ratio (VFDR) achieved over different number of hops for the Akiyo test sequences and live camera feed. We measure the VFDR at two layers: (i) at the network layer - it is the number of video frames that have been successfully received by the receiver, and (ii) at the application layer - the VFDR is the number of video frames that are received by the application and displayed successfully on the screen. It should be noted that the application usually maintains a fixed size (configurable, but fairly small) queue to buffer the received frames. When the phones can not draw the video frames to the screen fast enough, this queue can become full and starts to discard incoming video frames.
Secured Two Phase Geographic Greedy Forwarding (SecuTPGF) is a geographic greedy forward- ing protocol for transmitting multimedia data stream in Wireless Multimedia Sensor Networks (WMSN) in a secure and reliable manner. Cryptographic and MAC authentication mechanisms are used to implement security for both node and message authentication. In this paper, a modified version of SecuTPGF, the GSTP routing provides security for both node and message authentica- tion by using MD5 algorithm with a reduced computation power. In SecuTPGF, two different algo- rithms are used for node and message authentication, and GSTP routing uses “MD5Algorithm” for both node and message authentication. Using MD5 algorithm for node and message authentication, the average number of transmission paths increased and average number of hops used for trans- mission decreased when compared to the SecuTPGF. By conducting security analysis & evaluation experiments, the effectiveness of GSTP routing algorithm is proved.
242 The DSDV protocol requires that each mobile station in the network must constantly advertise to each of its neighbours, its own routing table. Since, the entries in the table my change very quickly, the advertisement should be made frequently to ensure that every node can locate its neighbours in the network. This agreement is placed, to ensure the shortest number of hops for a route to a destination; in this way the node can exchange its data even if there is no direct communication link.
The ExOR protocol combines routing with MAC-layer functionality . Routers send broadcast packets in batches, with no previous route computation. Packets are transmitted in batches to reduce protocol overhead. Besides, broadcasting data packets improves reliability because only one intermediate router is needed to overhear a transmission. Nevertheless, it does not guarantee that packets are received, because they are not acknowledged. Thus, an additional mechanism is needed to indicate correct data reception. Among the intermediate routers that have heard the transmission, only one retransmits at a time. The source router defines a forwarding list and adds it to the header of the data packets. This list contains the addresses of neighbors, ordered by forwarding priority. Routers are classified in the forwarding list according to their closeness to the destination, computed by a metric similar to ETX. The metric used by ExOR only considers the loss rate in the forward direction because there are no acknowledgments. Upon reception of a data packet, the intermediate router checks the forwarding list. If its address is listed, it waits for the reception of the whole batch of packets. It is possible, however, that a router does not receive the entire batch. To cope with this problem, the highest-priority router that has received packets forwards them and indicates to the lower-priority routers which packets were transmitted. Consequently, the lower-priority routers transmit the remaining packets, avoiding duplicates. The transmissions are performed until the destination indicates the reception. The Resilient Opportunistic MEsh Routing protocol (ROMER)  combines long-term shortest-path or minimum- latency routes with on-the-fly opportunistic forwarding to provide resilient routes and to deal with short-term variations on medium quality. ROMER computes long-term routes and opportunistically expands or shrinks them at runtime to fully exploit short-term higher-quality links. Long-term routes are computed using the minimum number of hops or the minimum average delay. Unlike ExOR, ROMER transmits on a packet basis to enable faster reaction to medium variations. The highest-throughput route is chosen according to the maximum PHY rate as indicated by the MAC layer.
Mello et al.  present a heuristic called Joint approach for Improving Load balancing and Path length (JILP) for a bi-objective optimization of WMN, where the routes with shortest paths are selected. JILP is responsible for finding solutions for a integer linear multi-objective pro- gramming model that can reduce the number of hops and bottlenecks of the routes in a WMN. This model is able to maintain the lowest bottlenecks in the net- work, and keep control of the routing stability to avoid any unnecessary change of routes. The routing approach is then combined with a channel assignment algorithm to improve network efficiency. However, this approach does not take into account that the scenario is influ- enced by natural physical phenomena, such as inter- ference and signal fading. This may not be enough to provide a good performance, largely because it is sub- ject to signal quality degradation in some regions of the network.
In this section, we evaluate with simulation the effective- ness of our proposed system for a physical network shown in Fig. 6. In this physical network, the number of nodes is 12 and the number of links is 18. Moreover, for tourist spots, virtual networks are constructed over the physical network by using our proposed topology design explained in Sect. IV. In each virtual network, the amount of resources that is allocated to a link between two tourist spots is set to 15, and the amount of resources that is allocated to other links is set to 2. For the performance comparison, we evaluate the performance of another virtual network construction method that is called Minimized hops in the following. In the minimized hops method, star topologies are designed so as to minimize the total number of hops from a tourist spot whose promotional video is delivered to other spots.
This paper presented and simulated a CCN model for IoT based SC application, in which a hybrid naming scheme is proposed where contents are named through the use of both (1) hierarchical and (2) flat naming schemes. The hierarchical component takes the domain name, location, task and device name in URL style. By using ‘task’, push support is added in the native CCN protocol. The flat component is used to provide integrity and it is computed through the FNV-1a hash of the device name and Data. The communication loop problem associated with CCN protocol is eliminated by implementing ‘unicast’ protocol on the source nodes. Mobile IoT nodes are used for delivery of Interest and Data packets to nodes that are not in the range of sink node. The proposed naming scheme is evaluated for IoT-SC having both static and mobile nodes and results revealed the significant gain in terms of success rate and number of transmissions of Interest packets, latency, number of hops and interest aggregation. Furthermore, both attributes and properties of contents and nodes can be incorporated to strengthen the scope of the scheme .
Figure 7 shows the average number of hops of content download as a function of the parameter k of the proposed method in the USA topology model. From this figure, we observe that the average number of hops decreases with the value of the parameter k until k reaches 2 . Then the average number of hops increases with the value of the parameter k. When k is small, i.e., k ≤ 0, the proposed method sends request packets to management nodes even if the number of hops to a content server is smaller than that to a management node. Therefore, the average number of hops increases in this case. On the other hand, when k is large, i.e., k ≥ 3, the proposed method tends to directly send request packets to content servers even if the number of hops to a content server is larger than a management node. In this case, the proposed method cannot utilize management nodes and cached contents. As a result, the average number of hops of content download increases. When k ≥ 6, the performance of the proposed method is the same as the passive download method. When k = 2 , the proposed method shows the best performance for any value of m , which is smaller than the average number of hops of the passive download method.
in Routing, the interference parameter and Energy levels of sensor nodes should be involved In line with both interference and energy reduction. The remaining energy of sensors must be calculated to consider and involve energy. The main challenge of reducing interference is the minimum overlap in radio area of those sensors, which transmit data simultaneously. If we want to maximize network lifetime, the state of energy consumption must be regarded too. A tradeoff is required to consider all these two parameters simultaneously. First, a certain area for candidate sensor range for transmission is determined to set a tradeoff over proposed method. Then the three following stages are evaluated to find search area based on the number of hops between source and destination: First, a covering area and an interference area are illustrated for source and destination nodes, which are equal to a circle with center of target node, and a radius with the maximum amount of transmission range (d max ), a circle with the center of target node and a radius with the amount of interferences range (d I )respectively 24 . The search area is formed