Search Packet Research Articles

Trail-Based Search for Efficient Event Report to Mobile Actors in Wireless Sensor and Actor Networks.

In wireless sensor and actor networks, when an event is detected, the sensor node needs to transmit an event report to inform the actor. Since the actor moves in the network to execute missions, its location is always unavailable to the sensor nodes. A popular solution is the search strategy that can forward the data to a node without its location information. However, most existing works have not considered the mobility of the node, and thus generate significant energy consumption or transmission delay. In this paper, we propose the trail-based search (TS) strategy that takes advantage of actor’s mobility to improve the search efficiency. The main idea of TS is that, when the actor moves in the network, it can leave its trail composed of continuous footprints. The search packet with the event report is transmitted in the network to search the actor or its footprints. Once an effective footprint is discovered, the packet will be forwarded along the trail until it is received by the actor. Moreover, we derive the condition to guarantee the trail connectivity, and propose the redundancy reduction scheme based on TS (TS-R) to reduce nontrivial transmission redundancy that is generated by the trail. The theoretical and numerical analysis is provided to prove the efficiency of TS. Compared with the well-known expanding ring search (ERS), TS significantly reduces the energy consumption and search delay.

Hardware Accelerators Targeting a Novel Group Based Packet Classification Algorithm

Packet classification is a ubiquitous and key building block for many critical network devices. However, it remains as one of the main bottlenecks faced when designing fast network devices. In this paper, we propose a novel Group Based Search packet classification Algorithm (GBSA) that is scalable, fast, and efficient. GBSA consumes an average of 0.4 megabytes of memory for a 10 k rule set. The worst-case classification time per packet is 2 microseconds, and the preprocessing speed is 3 M rules/second based on an Xeon processor operating at 3.4 GHz. When compared with other state-of-the-art classification techniques, the results showed that GBSA outperforms the competition with respect to speed, memory usage, and processing time. Moreover, GBSA is amenable to implementation in hardware. Three different hardware implementations are also presented in this paper including an Application Specific Instruction Set Processor (ASIP) implementation and two pure Register-Transfer Level (RTL) implementations based on Impulse-C and Handel-C flows, respectively. Speedups achieved with these hardware accelerators ranged from 9x to 18x compared with a pure software implementation running on an Xeon processor.

The Distribution of Route Search Packet Flows in Ad Hoc Networks

The amount of route search (RS) packets in Ad Hoc networks depend on the usage of network node location data and signal strength levels for defining response zones and sending RS packets. In case when route response zones are not restricted in every next step of the routing process, the number of generated RS packets grows according to the geometric progression. When node location data and signal strength level is used, the number of RS packets generated at the next routing step increases according to the arithmetic progression or may be constant. It has been shown in the paper that response zone restrictions help to reduce the number of generated RS packets significantly in high density network, while exploiting the location data and signal strength level in lower density network is less efficient. Ill. 5, bibl. 10, tabl. 1 (in English; abstracts in English and Lithuanian). http://dx.doi.org/10.5755/j01.eee.115.9.744

Ballooning: An Agent-Based Search Strategy in Wireless Sensor and Actor Networks

Due to the actor mobility and duty cycle of sensor nodes, the data forwarding from sensor nodes to mobile actors is a challenging issue. Motivated by the research results in multi-agent systems, we consider the search packet as an agent moving in the network to search mobile actors. Then a strategy called ballooning is proposed to control the search process. The theoretical and numerical results show that the ballooning strategy can forward the search packet to mobile actors with bounded delay and efficient energy consumption.

Uncovering Spoken Phrases in Encrypted Voice over IP Conversations

Although Voice over IP (VoIP) is rapidly being adopted, its security implications are not yet fully understood. Since VoIP calls may traverse untrusted networks, packets should be encrypted to ensure confidentiality. However, we show that it is possible to identify the phrases spoken within encrypted VoIP calls when the audio is encoded using variable bit rate codecs. To do so, we train a hidden Markov model using only knowledge of the phonetic pronunciations of words, such as those provided by a dictionary, and search packet sequences for instances of specified phrases. Our approach does not require examples of the speaker’s voice, or even example recordings of the words that make up the target phrase. We evaluate our techniques on a standard speech recognition corpus containing over 2,000 phonetically rich phrases spoken by 630 distinct speakers from across the continental United States. Our results indicate that we can identify phrases within encrypted calls with an average accuracy of 50%, and with accuracy greater than 90% for some phrases. Clearly, such an attack calls into question the efficacy of current VoIP encryption standards. In addition, we examine the impact of various features of the underlying audio on our performance and discuss methods for mitigation.

On the scalability of expanding ring search for dense wireless sensor networks

Expanding Ring Search (ERS) is a prominent technique used for information discovery in multi-hop networks where the initiator of the search is unaware of any of the γ locations of the target information. ERS reduces the overhead of the search by successively searching for a larger number of hops starting from the location of search initiator. Even though ERS reduces the overhead of the search compared to flooding, it still incurs a very high cost which makes it unsuitable especially for energy constrained networks like Wireless Sensor Networks (WSNs). Moreover, the cost of search (number of transmitted bytes) using ERS increases with node density, which limits its scalability in densely deployed WSNs. In this paper, we apply the principles of area coverage to ERS and propose a new protocol called Coverage based Expanding Ring Search (CERS) for energy efficient and scalable search in WSNs. CERS is configurable in terms of energy–latency trade-off which enables it applicable to varied application scenarios. The basic principle of CERS is to route the search packet along a set of ring based trajectories that minimizes the number of messages transmitted to find the target information. The transmissions are performed such that only a subset of total sensor nodes transmit the search packet to cover the entire terrain area while others listen. We believe that query resolution based on the principles of area coverage provides a new dimension for conquering the scale of dense WSNs. We compare CERS with existing query resolution techniques for unknown target location such as ERS, Random walk search, and Gossip search. We prove by both analysis and simulation that CERS is highly scalable, the cost of search is independent of node density, the energy consumed is much lower than that of the existing search techniques, and CERS always finds the nearest replica of the target information under high node density.

Energy Efficient and Scalable Search in Dense Wireless Sensor Networks

In this paper, we consider the problem of information discovery in a densely deployed wireless sensor network (WSN), where the initiator of search is unaware of the location of target information. We propose two protocols: increasing ray search (IRS), an energy efficient and scalable search protocol, and k-IRS, an enhanced variant of IRS. The priority of IRS is energy efficiency and sacrifices latency whereas k-IRS is configurable in terms of energy-latency trade-off and this flexibility makes it applicable to varied application scenarios. The basic principle of these protocols is to route the search packet along a set of trajectories called rays that maximizes the likelihood of discovering the target information by consuming least amount of energy. The rays are organized such that if the search packet travels along all these rays, then the entire terrain area will be covered by its transmissions while minimizing the overlap of these transmissions. In this way, only a subset of total sensor nodes transmits the search packet to cover the entire terrain area while others listen. We believe that query resolution based on the principles of area coverage provides a new dimension for conquering the scale of WSN. We compare IRS and k-IRS with existing query resolution techniques for unknown target location such as expanding ring search (ERS), Random walk search, and variants of Gossip search. We show by analysis, simulation, and implementation in testbed that IRS and k-IRS are highly scalable, the cost of search (total number of transmitted bytes) is independent of node density, and it is much lower than that of existing proposals under high node density.

Asymptotics of search strategies over a sensor network

We consider the problem of a user searching for information over a sensor network, where the user does not have prior knowledge of the location of the information. We consider three information search strategies: i) a source-only search, where the source (user) tries to locate the destination by initiating search which propagates as a continuous time random walk (Brownian motion); ii) a source and receiver driven "sticky" search, where both the source and the destination send a search or an advertisement, and these leave a "sticky" trail to aid in locating the destination; and iii) where the destination information is spatially cached (i.e., repeated over space), and the source tries to locate any one of the caches. After a random interval of time with average t, if the information is not located, the search times-out, and the search is unsuccessful. For a source-only search, we show that the probability that a search is unsuccessful decays as (log(t))/sup -1/. When both the source and the destination send search packets or advertisements, we show that the probability that a search is unsuccessful decays as t/sup -5/8/. Further, faster polynomial decay rates can be achieved by using a finite number of searches or advertisements. Finally, when a spatially periodic cache is employed, we show that the probability that a search is unsuccessful decays no faster than t/sup -1/. Thus, we can match the decay rates of the source and the destination driven search with that of a spatial caching strategy by using an appropriate number of search packets. The sticky search as well as caching utilize memory that is spatially distributed over the network. We show that spreading the memory over space leads to a decrease in memory requirement, while maintaining a polynomial decay in the search failure probability. In particular, we show that the memory requirement for spatial caching is larger (in an order sense) than that for sticky searches. This indicates that the appropriate strategy for searching over large sensor networks with little infrastructure support would be to use multiple search packets and advertisements using the sticky search strategy.

Self-learning route selection scheme using multipath searching packets in an OBS network

In an optical burst switching (OBS) network, some contention resolution schemes at a core router have been proposed. However, in terms of the optical device technology, it is difficult to implement the contention resolution schemes such as optical buffers at a core router. In this paper, we propose the scheme that reduces the probability of burst contention by controlling the route at an edge router without resolving burst contention at a core router. Each edge router learns a suitable route to the destination edge router autonomously by using newly employed feedback packets and search packets. Due to the self-learning at each edge router, the traffic load is distributed in an OBS network. Therefore, our proposed scheme can reduce the probability of burst contention. According to computer simulations, under nonuniform traffic, our proposed scheme can reduce approximately one decade smaller burst loss probability compared with the conventional shortest path routing method.

Recherche dynamique d'agent dans la couche réseau par multipoint orienté

Many protocols and applications need a discovery mechanism to enable a given client node to locate one or several specific nodes involved in the same communication. However, there is no protocol ready to fulfill this service at the network layer. Every protocol usually implements its own solution. In particular, multicast protocols often use a search technique called expanding ring search. This method searches for those specific nodes in all directions and thus uses much bandwidth. However a typical search can usually restrict its scan in a specific direction. To answer this problem, we propose a network search protocol in replacement of the expanding ring search. This protocol is based on an oriented multicasting protocol in order to ensure an efficiency higher than the expanding ring search. The oriented multicasting principle is to channel the multicasting of search packets towards a special node, involved in the communication, in order to scan only a limited area. We provide comparative simulation results between our protocol and the expanding ring search.