TT normally refers to the process whereby two or more devices work in conjunction to estimate the location of an object. Although there are instances in which a single device can be used to track an object, we are interested in the case where multiple devices are employed to reduce uncertainty about the object’s position. A traditional TT application focuses on the design and implementation of the corresponding algorithms as a signal processing problem. To this regard, the (distributed) system’s operation is expected to remain unchanged. However, if the circumstances surrounding the object being tracked change, it is possible that the performance

 of the current (static) approach

could be compromised to the point of becoming ineffective. However, an MA approach would enable system operators to deploy distinct TT algorithms on demand to adapt to the prevailing

circumstances. It could be argued  that a simple remote method invocation (RMI)

mechanism meets the necessary requirements to implement this application, in which sensor nodes in the tracking region would maintain communications African Mango with a control unit outside of the WSN employed to orchestrate the task. However, it is clear that this approach would

incur additional delay during the communications between the WSN control unit and the respective nodes.

Several solutions to the TT problem that employ MAs have been proposed in the

literature. In Ref. [39], moving targets are tracked by MAs by employing leather furniture a simple ”

trilateration” algorithm, and the result is periodically sent to a server that stores the targets’ location. snoring chin strap To achieve this, a node employs its own location measurement baby shower cakes information and combines it with the readings obtained by two of its direct neigh- bors to produce a target location estimate. Figure 5A illustrates this approach, where the three-circled areas specify the possible  positions of the target object based on the measurements taken by an equal number of MAs. One of these agents is referred to as the “mother agent,” whereas the other two are  referred to as “child agents” that are controlled by the mother agent to work cooperatively to obtain a better estimate of the target object’s location. Figure 5A also shows that the mother agent temporarily stationed at node

A dispatches the child agents to nodes B and C to help locate the target object. The child agent at B ends pokies operations when the received signal strength at this node decays beyond a certain threshold, whereas de D receives a new child agent, as depicted in Fig. 5B. Later, the mother agent itself decides to migrate to node C to avoid losing track of the moving target. At this point, all child agents terminate, and new ones are dispatched to nodes D and E, as shown in Fig. 5C. From this example, it follows that multiple sole f80 child agents can be deployed to track a moving object, and that their number can vary depending on the number of WSN nodes present in the monitored region. An

sole f63 alternative approach proposed in Ref. [40] also promotes dispatching an MA to track a moving object, as shown in Fig. 6. Upon migrating to a sensor node, the agent collects the necessary information to gradually

This approach relies on current global network total gym xls information to derive a possible

migration path before an MA is dispatched. Two methods that address this problem were presented in Ref. [46]: local closest first (LCF) and global closest first (GCF), both of  which assume that out of the nodes to be visited, the executing one is the closest to the gateway. For this reason, LCF first searches quick payday loans for the node that is closest to the current node, whereas GCF does so for the node closest to the gateway. Alternative solutions also exist. For instance, a genetic algorithm is presented in Ref. [47] to devise MA itineraries for  WSNs, which assumes that each sensor node can be visited only once to reduce the search space. This solution achieves global optimi- zation,

though it is a computationally heavy one whose actual suitability in resource constrained nodes is debatable.

Our previous descriptions of static MA itinerary planning solutions reveal that they may be unsuitable for WSNs that experience  varying conditions if the global information stored at the gateway becomes outdated in the presence of continuous changes in the underlying environment. On the contrary, dynamic itinerary planning enables MAs to determine which node to visit as it hops through its migration path. To achieve this, trade-offs between the migration plan change  costs and possible efficiency degradations should be taken into account. For instance, researchers in Ref. [40]

promote a dynamic planning method that achieves progressive fusion accuracy without incurring excessive costs. To this end, the dynamic itinerary planning approach ensures that the visited sensor nodes (1) have enough battery power energy, (2) require minimum energy consumption for the MAs migration, and (3) yield significant information gain. As discussed before, one of the objectives of the MA should be visiting sensor nodes that reduce uncertainty to shorten the migration path, reduce bandwidth usage, and decrease task completion delay.

which we introduced as a WSN. To this effect, energy efficiency becomes one of the core design principles for all research done in this area, given that these WSN devices are generally powered by batteries. Moreover, many commercial WSN platforms are comprised by devices with severe memory and processing power limitations. These and other circumstances motivate research of flexible and improved schemes that allow WSNs to be reprogrammed when a new data collection/dissemination methodology is needed. At the same time,  it is important to determine whether these new schemes are practicable from an engineering point of view to ensure that neither performance nor data integrity is compromised. Given that the primary role of WSNs is data collection, it follows that environmental  monitoring and people/object surveillance comprise a good portion of their intended applications. In this section, we explore the intricacies that WSN researchers and engineers encounter when architecting an MA-based Bose Companion 3 solution aimed at monitoring and surveillance applications. In particular, we study VSNs and target tracking (TT) harman kardon soundsticks ii applications, both of which provide a prime example of how MA technology can be employed.

Using WSNs for Image Retrieval

One of the most challenging tasks logitech z-5500 that can be observed in WSNs is image retrieval. To this end, both heavy image preprocessing load and high bandwidth usage have adverse consequences in the battery lifetime of sensor devices. In logitech x-540 addition to this, such amount of data has the potential to clog the wireless link (s) when being forwarded to the VSN gateway for subsequent processing, as discussed in Section 1. As a result, a number of approaches have been promoted in the literature to retrieve images or video from WSNs [33, 34]. Some of the latest advancements in this area  include Cyclops [35] and SensEye [36], among others, which are image processing testbeds especially developed for WSN use [37]. A quick survey of existing VSN schemes reveals that they rely on source coding and multipath forwarding schemes to  achieve their task. Because of the bandwidth limitations encountered in commercial WSN platforms employing IEEE 802.15.4 radio technology that supports up to 250Kbits/s data rates, there will always be a hard threshold for the amount of data  that these and other schemes will be able to transport from a sensor device to the gateway.

From the above discussion, we can see that replica bags MAs are well positioned as a plausible solution to leverage the performance of VSNs [38]. To this end, we recently proposed a solution whereby an agent is dispatched to the node that initially captures an image that needs to be analyzed and executes a preprocessing algorithm to obtain the picture’s ROI, as depicted in Fig. 4. There, we can observe that the MA carries with it image segmentation and preanalysis codes to isolate a portion of the original image and perform a preliminary assessment procedure before forwarding the image segment to the VSN’s gateway. As a result, an otherwise large volume of image data originating at any region of the VSN can be significantly reduced to a much smaller, manageable one. The main feature introduced by the MA approach here is that if the conditions surrounding the monitored environment vary, then a new MA with an alternative image segmentation algorithm can be dispatched to the corresponding VSN devices to maintain the overall system’s efficiency.

As mentioned before, this chapter describes our latest MA technology advances in WSN and in mobile computing environments that employ radio frequency identifi- cation (RFID) technology. In Section 2, we look into the design issues encountered when engineering both MASs and applications in WSNs. We survey the particular example of video sensor networks (VSNs) as a WSN application with unique traits that can be favored by employing MAs. Interest in VSNs stems from the commercial application of video surveillance in deployment settings where intrusions are extremely rare, there is no supporting infrastructure (i.e., electricity), and there is no personnel to monitor the operation of the system in a permanent basis [30,31]. As a result, MAs can be employed to provide an autonomous, low-power mode of operation. We dissect the MAS design functionality into the following components: architecture, MA itinerary planning, middleware system design, and agent coopera- tion methodology. This classification spans low- and high-priority design issues and assists in the creation of an MAS that can be useful in an ample range of applica- tions. We argue that flexible trade-offs between energy and delay can be reached, depending on the specific requirements set by the application.

In Section 3, we present the results of our investigation after putting theory into practice through

in WSN devices characterized by having severe hardware constraints. Here, we

detail the groundwork of our approach and its unique language constructs that minimize its operating cost. Wiseman was coded in the NesC language to produce a TinyOS ver. 1.x [32] binary image that spans 19KB of code and 3KB of SRAM. In addition, we elaborate on the distinct agent migration methodologies that the interpreter supports and present some performance evaluations regarding consumed bandwidth and internode hopping delay.

In Section 4, we advance a novel idea that relies on RFID technology as an enabler of diverse ambient intelligence applications. Given their small size and low cost characteristics, RFID tags can be easily embedded into consumer electronics devices in support of smart spaces. To this effect, RFID tags would readily enable the immediate identification of persons and objects to rapidly retrieve prestored, smart space configurations from a database and enact system personalization actions. However, there are problems that need to be sorted out with regard to the personaliza- tion of services and system configuration when person moves from one ambient intelligence environment into another. One of the major impediments for achieving this functionality is the way in which existing RFID systems function, which com- plicates their straightforward adaptation into real-world dynamics so as to fulfill application-specific requirements. We refer to this as identification-centric RFID system (IRS), which stores and forwards simple ID values that are referenced during a simple database lookup process to retrieve relevant information about the object that carries the corresponding ID tag. To address this problem, we promote advancing IRS into CRS—a code-centric RFID system, whereby actions are dynamically encoded and stored in RFID tags that possess improved memory capabilities. We argue that this innovative approach facilitates the operation of the implementing system to enact actions on demand in environments comprised by distinct objects, and under varying circumstances to achieve improved scalability. We present an E-healthcare manage- ment application that exemplifies the potential of our proposed CRS approach, and its importance in a smart space scenario. In Section 5, we conclude this chapter by summarizing our experiences using MA technology to solve distinct tasks in wireless networks and discussing possible improvements and areas of future research.in WSN devices characterized by having severe hardware constraints. Here, we detail the groundwork of our approach and its unique language constructs that minimize its operating cost. Wiseman was coded in the NesC language to produce a TinyOS ver. 1.x [32] binary image that spans 19KB of code and 3KB of SRAM. In addition, we elaborate on the distinct agent migration methodologies that the interpreter supports and present some performance evaluations regarding consumed bandwidth and internode hopping delay.

In Section 4, we advance a novel idea that relies on RFID technology as an enabler of diverse ambient intelligence applications. Given their small size and low cost characteristics, RFID tags can be easily embedded into consumer electronics devices in support of smart spaces. To this effect, RFID tags would readily enable the immediate identification of persons and objects to rapidly retrieve prestored, smart space configurations from a database and enact system personalization actions. However, there are problems that need to be sorted out with regard to the personaliza- tion of services and system configuration when person moves from one ambient intelligence environment into another. One of the major impediments for achieving this functionality is the way in which existing RFID systems function, which com- plicates their straightforward adaptation into real-world dynamics so as to fulfill application-specific requirements. We refer to this as identification-centric RFID system (IRS), which stores and forwards simple ID values that are referenced during a simple database lookup process to retrieve relevant information about the object that carries the corresponding ID tag. To address this problem, we promote advancing IRS into CRS—a code-centric RFID system, whereby actions are dynamically encoded and stored in RFID tags that possess improved memory capabilities. We argue that this innovative approach facilitates the operation of the implementing system to enact actions on demand in environments comprised by distinct objects, and under varying circumstances to achieve improved scalability. We present an E-healthcare manage- ment application that exemplifies the potential of our proposed CRS approach, and its importance in a smart space scenario. In Section 5, we conclude this chapter by summarizing our experiences using MA technology to solve distinct tasks in wireless

networks and discussing possible improvements and areas of future research.

in WSN devices characterized by having severe hardware constraints. Here, we

detail the groundwork of our approach and its unique language constructs that minimize its operating cost. Wiseman was coded in the NesC language to produce a TinyOS ver. 1.x [32] binary image that spans 19KB of code and 3KB of SRAM. In addition, we elaborate on the distinct agent migration methodologies that the interpreter supports and present some performance evaluations regarding consumed bandwidth and internode hopping delay.

In Section 4, we advance a novel idea that relies on RFID technology as an enabler of diverse ambient intelligence applications. Given their small size and low cost characteristics, RFID tags can be easily embedded into consumer electronics devices in support of smart spaces. To this effect, RFID tags would readily enable the immediate identification of persons and objects to rapidly retrieve prestored, smart space configurations from a database and enact system personalization actions. However, there are problems that need to be sorted out with regard to the personaliza- tion of services and system configuration when person moves from one ambient intelligence environment into another. One of the major impediments for achieving this functionality is the way in which existing RFID systems function, which com- plicates their straightforward adaptation into real-world dynamics so as to fulfill application-specific requirements. We refer to this as identification-centric RFID system (IRS), which stores and forwards simple ID values that are referenced during a simple database lookup process to retrieve relevant information about the object that carries the corresponding ID tag. To address this problem, we promote advancing IRS into CRS—a code-centric RFID system, whereby actions are dynamically encoded and stored in RFID tags that possess improved memory capabilities. We argue that this innovative approach facilitates the operation of the implementing system to enact actions on demand in environments comprised by distinct objects, and under varying circumstances to achieve improved scalability. We present an E-healthcare manage- ment application that exemplifies the potential of our proposed CRS approach, and its importance in a smart space scenario. In Section 5, we conclude this chapter by summarizing our experiences using MA technology to solve distinct tasks in wireless

networks and discussing possible improvements and areas of future research.

A myriad of MA-based solutions ranging from the network to the application layer were proposed throughout the literature, mostly from the mid-1990s to the early 2000s when the first investigations into MASs and their potential applicability took place [7]. A great deal of research focused on the high-level application aspects of this technology (e.g., [8]), whereas other efforts were aimed at a subject widely known as active networking [9]. Several MASs were proposed, as per the wide range of possible applications that MAs could support. The majority of these systems were  built to run on the Java virtual machine (JVM). In fact, ome contemporary Java- based platforms such as JXTA natively support code mobility in the form of MAs [10]. In this section, we summarize the most important aspects of their deployment, instead of engaging in a detailed review of individual MASs. stationary bike stand applications are apparent because it has the potential to significantly reduce (1) bandwidth consumption incurred by network management overhead and (2) overall power consumption to help extend battery lifetime, as explained in Section 1.2. One particular technology that exemplifies the benefits introduced by using MAS is WSNs. In brief, using MAs in WSNs may facilitate application programmability (also known as retasking) and collaborative signal and data processing. The MAS approach has a good potential to decrease bandwidth use (and its associated  battery consumption), contrary to conventional WSN operations that rely heavily on the client–server communications model. WSNs have been the focus of much attention in the research community for nearly a decade [18–20], which is driven in part by a large number of theoretical and practical challenges. WSNs are intended to support specialized applications. However, it is tempting to try and employ a single WSN deployment to implement multiple applications due to the high cost of acquiring hundreds or even  thousands of sensor nodes, if so necessitated by the application, or to cover a wide geographical area as proposed in Refs. [21,22]. The problem with this approach is that storing a multifunctional program to support diverse applica- tions incurs significant memory utilization, which could be alleviated by employing the MAS funny t shirts approach. The advantage of using MAS here is that it enables the deployment of different types of agents to accomplish various tasks without the need to reprogram the WSN’s nodes. It could be argued that the MAS approach is not much different from a multifunctional program for

WSN applications. However, the multifunctional program approach will always be limited to the specific applica- tions it has been built to support. However, the MAS approach provides the same functional value of a virtual machine, thus allowing MA deployment for applica- tions that might not have been considered. In other words, it enables adaptation to unforeseen circumstances, which can be no no hair removal considered an inherent trait of environ- ments monitored by WSN hardware.

Even though MASs were extensively studied by  prominent researchers, to a certain extent it failed to fulfill the high expectations that many had placed on it [23]. Nowadays, MA research is still well positioned to enable contributions with a significant value, particularly in an area commonly known as smart spaces that has drawn considerable interest as of late [24–26]. This term is used by pervasive computing researchers when referring to digital signage intelligent environments enabled by con- sumer electronics and appliances with embedded devices whose behavior can vary as a result of their context awareness capabilities. Smart space applications are in turn enabled by ambient intelligence

—a group of technologies assembled to provide an automated, personalized Data Mining Software service or experience to one or more persons [27–29]. To this end, advances in electronics miniaturization technology enable the deploy- ment of sensors and data processing devices with limited capabilities to create abstract representations of the surrounding environment, along with other devices

that can be used to provide a personalized, replica watches context-aware service. In other words, a smart space can be envisaged as a complex, interactive system that enacts one or more actions by using one or more of the surrounding devices as outputs, in accordance to a series of inputs provided by intelligently networked sensors. This is a relatively new technology with both growing interest in the research community and a vast potential for commercialization. However, a great deal of research needs to be conducted before experimental devices implementing this technology leave the industry and university labs to become consumer devices available to the general  public. It is not hard to see that a smart space is actually a hybrid system formed by both hardware and software deployed in and around people in a distributed fashion. Therefore, we envision using MA technology as a prime candidate supporting complex, mobile Ambient Intelligence systems. JVM-based MASs were highly popular for applications that required portability and support to accomplish complex tasks. This provided a programming and execu- tion platform with unmatched flexibility that enabled MAS deployment to support a wide variety of applications [11,12]. Nonetheless, performance issues and security vulnerabilities were important concerns in applications that employed MAS for cellular phones and personal digital assistants sporting lightweight versions of the JVM, as mentioned before [13]. In addition, their overall effectiveness was some-  times compromised by distinct versions and flavors of the JVM installed in personal devices. This was not the problem of custom-built MAS, which provided a more homogeneous platform for implementing agent-based applications. However, these systems were less portable and were built for specific types of applications. It is also worth noting that some MA investigations did not involve any particular MAS and instead focused on other important aspects, such as migration strategy [14,15]. In fact,

Essay writing some early work advanced alternative MA schemes for wireless and mobile networks management without actually promoting a particular system [16]. In addition, some agent research targeted web-based applications for enhanced service discovery and composition (i.e., the combination of two or more services to form one single application) [17], though subsequent years saw a significant decrease in MA and  MAS research activity. Nevertheless, enough interest remained on the subject to motivate sporadic research efforts on distinct networking technol- ogies. In our case, the benefits of employing MA technology in wireless networks

1.2 Advantages and Disadvantages of Using MAs The benefits and drawbacks of the MA approach were extensively discussed in the initial years of its research. In general, there are some wedding rings advantages that are attributable to all agent types, whereas others are more specific. For instance, compactness is oftentimes referred to as an inherent MA characteristic, though this is not always the case. For instance, an MA coded to perform a complex brokering task requires that a significant amount of functionality be implemented into it to deal with a wide variety of possible situations for the transactions it supports. However, MAs used for active networking tasks (e.g., routing) can be significantly more compact because they are targeted at specific tasks with well- known outcomes. Another advantage regularly associated to using agents is band- width savings, which can be achieved if an efficient agent migration policy is employed. However, it is possible that the bandwidth overhead incurred by moving a relatively large agent could offset the one incurred by using a simple message- passing scheme, depending on the application. Still, the bandwidth-savings potential remains by far one of the most compelling reasons for using agents [6].Figure 3 exemplifies the bandwidth savings-feature by showing both a traditional and an MA-based approach for collecting data in a WSN. In the first case, the occurrence of an event as sensed by individual WSN nodes initiates the corresponding client–server interactions to send raw data to the WSN gateway or sink for subsequent analysis. In this approach, each client–server session incurs one photocopier rental data flow from source to destination, leading to higher bandwidth utilization. Moreover, this method places a higher burden in the nodes closer to the WSN gateway because their links observe heavy data traffic as compared to the wireless links located farther away from the gateway. Conversely, the mobile agent system (MAS) approach dispatches an agent to the WSN’s region of interest (ROI) where the event was observed. Once there, the MA processes data and sends back to the WSN gateway either a concise assessment of the situation or a digest of the analyzed data. This has the benefit of incurring a single traffic flow, in contrast to the client– server approach that observes multiple flows.

In addition to enabling bandwidth savings, MAs can also help reduce processing delay. Revisiting the example shown in Fig. 3, the actual data pooling process triggered by an event in a WSN region might require multiple interactions between the WSN gateway and the nodes involved. This obeys to the possibility of having a relatively large amount of data that have to be progressively transferred if, say, the first data block yields no conclusive results and one block or more need to be pooled from the corresponding devices until a result is found. Conversely, in the MA approach, the codes that actually process data migrate to the steriods devices that triggered the event, and the analysis is realized

in situ, so that no messages or data need to be sent back and forth from the devices to the WSN gateway. In addition, if a result is not found, the MA can migrate to another node to immediately begin analyzing more data, whereas using the message-passing approach entails initiating a new session between the WSN gateway and another treadclimber reviews device, followed by the respective data

transfer process. It is clear that the MA approach incurs less delay during its migration process than consecutively forwarding raw data segments. Resilience is yet another advantage that an MA-based solution can incorporate in environments whose behavior is unstable or highly uncertain. For instance, whereas a message- passing scheme incurs significant signaling to recover from failures during an ongoing data transfer session under adverse circumstances (e.g., in the presence of a noisy-channel, or frequent disconnections), an MA-based solution could have the agent monitor the channel conditions until the circumstances are favorable to migrate back to the WSN sink with the desired information.

The previous discussion provides some compelling reasons in favor of using MAs to solve distinct networking tasks. In fact, it is easy to see that these advantages are highly appealing Proactol for the case of wireless and mobile networks. However, there are important counterarguments against MA technology. For instance, bandwidth sav- ings can only be achieved if the size of one or more MAs performing a task is sufficiently compact to offset the bandwidth otherwise incurred by employing the message-passing mechanism. This might be hard to achieve if the MA is coded to provide added resilience, thereby sacrificing compactness as per the extra codes that implement this added feature. Another aspect that adds complexity to an MA-based solution is the migration strategy employed to visit multiple nodes, either throughout the network or in a portion thereof. An inefficient migration strategy incurs added bandwidth because of the total number of times that one or more MAs hop to accomplish a certain task. However, a carefully engineered migration strategy would ostensibly be capable of achieving better results. It thus follows that large- sized MAs implementing an inefficient migration strategy would result detrimental to the overall system’s performance. In addition, the effectiveness with which an MA solution provides resilience depends directly on the programmer’s ability to anticipate and deal with situations that the MA could encounter. In the message- passing mechanism, the respective communications protocol daemon running into an unexpected situation could simply reschedule the data transfer process at a later time if the current circumstances are unfavorable. Conversely, an MA could remain stranded at a remote node replica watches, perhaps unable to return to the network’s gateway upon encountering a situation that steered it into a deadlock state. An additional issue that can be used to argue against MA technology is that of security. To this regard, it is easy to see that an attacker could inject a malicious agent into a network to disrupt its normal operation (e.g., as a typical computer network virus). Conversely, one or more malicious device(s) could be used to disrupt an agent’s normal operation or to embed a malicious code segment into it. As a result, using MAs can be deemed a safer option in closed networks where access is controlled. Additionally, well- known cryptographic methods, such as digital signatures, can be readily employed to reduce to some extent the inherent security risks, though some performance degradations would be inevitable. However, this would be highly detrimental for network tasks requiring near real-time response, or in networks formed by devices with limited hardware resources, given that processing digital signatures entails additional memory custom t shirts availability and processing capabilities that increases power consumption.