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This paper presents a proof of concept for a generic middleware for heterogeneous sensor/actuator networks, which enables ad-hoc discovery, self-description exchange and basic interactions between heterogeneous devices. The main approach is to represent each device by a device-agent which knows its capabilities, constraints and policies, and is able to describe those to other devices on request. [ABSTRACT FROM PUBLISHER]

Combining energy harvesting with energy-aware scheduling enables perpetually operating sensor networks. The practical realization of this goal yet requires reliable and precise holistic online energy assessment. While the building blocks — assessing residual energy, predicting energy intake, and tracing energy consumption — have been studied in detail, the analysis of their interaction on a real platform has been neglected. This paper answers the question, whether these techniques can be easily joined to give a precise and correct picture of a sensor node's energetic state and behavior. For this purpose, we model the energy flow of a prototype energy-harvesting sensor node and evaluate the joint performance of state-of-the-art energy assessment based on a field test. We verify the system model and show the feasibility of holistic energy assessment, which tolerates small configuration errors, achievable with a combination of generic configuration and online calibration. We also analyze the feasibility of forecasting a node's future energetic state, and find that the presented method gives sufficient results for uniformly distributed consumption profiles. [ABSTRACT FROM PUBLISHER]

In this paper we present PCJ — a new library for parallel computations in Java inspired by the partitioned global address space approach. We present design details together with the examples of usage for basic operations such as a point-point communication, synchronization or broadcast. The PCJ library is easy to use and allows for a fast development of the parallel programs. It allows to develop distributed applications in easy way, hiding communication details which allows user to focus on the implementation of the algorithm rather than on network or threads programming. The objects and variables are local to the program threads however some variables can be marked shared which allows to access them from different nodes. For shared variables PCJ offers one-sided communication which allows for easy access to the data stored at the different nodes. The parallel programs developed with PCJ can be run on the distributed systems with different Java VM running on the nodes. In the paper we present evaluation of the performance of the PCJ communication on the state of art hardware. The results are compared with the native MPI implementation showing good performance and scalability of the PCJ. [ABSTRACT FROM PUBLISHER]

We compare the BQCD performance, a typical high performance computer application, using either the MPI or the Fraunhofer GPI communication library. In our analysis, we focus on the BQCD performance critical part covering 50 percent of the total program run-time. This is given by the computation of a four-dimensional nearest neighbor stencil operator in a domain decomposed simulation volume. Hence, BQCD is a typical representative for the broad class of stencil algorithms. In order to obtain optimal speedup, we overlap the communication with the computation and analyse the resulting run-times on two test systems. We introduce the overlap efficiency as a measure for the communication library's ability to overlap the communication with the computation. In the regime in which the raw communication latency is less than the raw computational time, the overlap efficiency should be equal to one. This regime depends on the problem size and on the number of used cores. Deviations from one show possible interferences of communication and computation induced by the communication library. Side effects which disturb the scalability in practice. As result, we find that GPI has overlap efficiency equal to one, i.e. it allows for perfect overlap and ideal scalability. The total runtime is equal to the time spent for the pure computation. For the same communication pattern, MPI has overlap efficiency less than one. It cannot hide the communication completely which results in a worse scalability in general. The GPI speedups in comparison with the equivalent MPI implementation are of the order of 20–30 percent. [ABSTRACT FROM PUBLISHER]

Wireless sensor networks are meant for monitoring in remote and inaccessible locations where it is not feasible to install conventional wired infrastructure. But the health monitoring system of such networks is relatively intangible to network administrators, because of their complex and unpredictable behavior. In this paper a survey on debugging techniques of wireless sensor networks are presented. The debugging tools are divided on the basis of their usage in application life cycle as pre-deployment, post-deployment and deployment-time validation. Based on the implementation strategies, the debuggers are further classified as software-based, hardware-based and hybrid. A comparative study is made on the debugging tools and a summary is provided in Table I. This paper also discusses about the key characteristics required for implementing an efficient debugging tool for wireless sensor network. [ABSTRACT FROM PUBLISHER]

This paper presents a Security View of the NOMOHi architecture (Node, Mobile, Hybrid, Intelligent), which combines devices capable of communicating simultaneously and collaboratively on two or more radio communications technologies, supporting processes of artificial intelligence for it. It describes how to work a NOMOHi sensor devices 802.11/Bluetooth/UWB and the WiMAX 802.16e/802.11 network services, and its potential practical applications for the distribution of satellite educational television content while it can be used simultaneously for the survival of communication in case of emergency in rural zones. The biggest problem is in the vulnerabilities of each of the communications technologies used in these networks simultaneously, low computational power of these devices, and of course to be low power consumption, means that this architecture poses immense challenges in terms to security: intrusion detection, trust relations and of course, Security routing protocols. In this paper, a description of how we are implementing a six-layer security architecture in a project designed for rural communications. [ABSTRACT FROM PUBLISHER]

Spatially distributed sensor nodes can be used to monitor systems and humans conditions in a wide range of application domains. A network of body sensors in a community of people generates large amounts of contextual data that requires a scalable approach for storage and processing. Cloud computing can provide a powerful, scalable storage and processing infrastructure to perform both online and offline analysis and mining of body sensor data streams. This paper presents BodyCloud, a system architecture based on Cloud Computing for the management and monitoring of body sensor data streams. It incorporates key concepts such as scalability and flexibility of resources, sensor heterogeneity, and the dynamic deployment and management of user and community applications. [ABSTRACT FROM PUBLISHER]

The paper presents a mKRISHI sensor network platform which is specifically designed to build a low cost wireless sensor network for precision agriculture applications. The Texas Instrument's CC2530, which is an IEEE 802.15.4 ZigBee compliant system-on-chip, has been used to provide a long range communication while making the sensor nodes more power efficient. The design and development of gateway has been also presented which connects the wireless sensor network to the back-haul network. The enclosure of the sensor node has been designed using the inexpensive PVC pipes which makes the entire solution more cost effective and feasible for the deployment in the outdoor environments like agriculture farms. It has been shown through the experiments that there is not significant attenuation in the received signal strength due to the enclosure using PVC pipes. The results obtained from the deployment of the sensor network over a period of two months has been presented to show the robustness of the proposed framework. [ABSTRACT FROM PUBLISHER]

Smart Cities offer a new approach for optimizing services, reducing costs, simplifying the management of Future Cities, enabling new services for citizens. In the Future Internet initiatives, Sensors Networks assume even more a crucial role, especially for making smarter cities. Sensors, becoming smart, will represent the peripheral elements of a complex future ICT world. However, due to the specific application field, smart sensors are very heterogeneous in terms of communication technologies, sensing features and elaboration capabilities. To overcome issues due to the high heterogeneity in this paper we present a new architecture able to make a dual abstraction of complex sensing infrastructures along with data they collect. An important key of this work is to provide a service at world wide level, that is scalable and flexible. The architecture implementation is based on Sensor Web Enablement standard specifications and makes use of the Contiki Operating System for accomplishing the Internet of Things. [ABSTRACT FROM PUBLISHER]

In this paper, data collection schemes with data aggregation for static sink are proposed in wireless sensor networks. According to the distribution of source nodes in whole sensor field, we use a block partition scheme and then each block selects a sensor node as local sink for the data collection of the local area. Furthermore, the local sink would transmit the data to the global sink after aggregating to achieve the purpose of reducing energy consumption. From the simulation results, it shows that our proposed methods are more efficient in the energy consumption and the data delivery ratio. [ABSTRACT FROM PUBLISHER]

Languages such as C and C++ use unsafe manual memory management, allowing simple bugs (i.e., accesses to an object after deallocation) to become the root cause of exploitable security vulnerabilities. This paper proposes Watchdog, a hardware-based approach for ensuring safe and secure manual memory management. Inspired by prior software-only proposals, Watchdog generates a unique identifier for each memory allocation, associates these identifiers with pointers, and checks to ensure that the identifier is still valid on every memory access. This use of identifiers and checks enables Watchdog to detect errors even in the presence of reallocations. Watchdog stores these pointer identifiers in a disjoint shadow space to provide comprehensive protection and ensure compatibility with existing code. To streamline the implementation and reduce runtime overhead: Watchdog (1) uses micro-ops to access metadata and perform checks, (2) eliminates metadata copies among registers via modified register renaming, and (3) uses a dedicated metadata cache to reduce checking overhead. Furthermore, this paper extends Watchdog's mechanisms to detect bounds errors, thereby providing full hardware-enforced memory safety at low overheads. [ABSTRACT FROM PUBLISHER]

To allow for rapid abstract development of algorithms, model-based tools are often used nowadays. These tools support design using predefined blocks, adaptation using parameters, simulation in a virtual environment and also generation of code for programming embedded devices. However, there is usually no direct connection between the embedded system and the model for programming and runtime control and monitoring. In this paper, we present a seamless tool chain for modelbased algorithm development, simulation and integration on an embedded system as well as runtime control and monitoring from model level. Based on our concept, the development of algorithms can largely be separated from the execution platform and its control and monitoring possibilities. Yet, it is possible to feedback monitored data to support the simulation. The concept is integrated and evaluated and its applicability for the development of an algorithm is demonstrated by means of an example from the field of wireless senor networks localization. We conclude that the outlined approach offers a simple opportunity to reduce development overhead. [ABSTRACT FROM PUBLISHER]

The issues of poor capacity, voltage and power quality experienced on long Single Wire Earth Return (SWER) electrical distribution systems have negative and sometimes expensive impacts on both the electrical distributor and their customers. Traditional mitigation methods employed include voltage regulators and fixed capacity Shunt Reactors and capacitors. To overcome inherent limitations of these traditional methods, the use of dynamic real and reactive power compensation devices based on 4 quadrant inverters is being investigated. This paper discusses the methodology and results of a modelling investigation into the effectiveness of these devices on a representative SWER system in Western Queensland. [ABSTRACT FROM PUBLISHER]

This paper presents a hybrid sensor network with both fixed nodes and mobile nodes for monitoring and protecting Milu Deer, a specific kind of rare animals in China. Our goal is to provide unprecedented fine-grained environmental and individual data for zoologists and explore potential problems in hybrid sensor networks. Total 116 nodes have been deployed up to now, which consists of 30 mobile nodes for monitoring Milu Deer's behaviour, 16 fixed nodes for monitoring environments, 69 fixed nodes for data relay and 1 sink node (or base station) for data gathering. Environmental nodes and relay nodes construct the fixed network infrastructure, which transfer environmental data and individual data to the sink node and then the server efficiently and reliably. Network protocols were designed using popular components and tailored for particular application scenarios. System performance was evaluated by both simulations and field experiments, which demonstrated the effectiveness of our monitoring system. [ABSTRACT FROM PUBLISHER]

Recent years have witnessed the emergence of Web services that publish data that can be used as globally shared data resources, and Web data stores offer data resources that can be shared and modified by users or groups. We think associative data representation among Web data elements is important for the reuse of the data for various purposes even when treating personal/group data. This paper aims to provide a general-purpose widget for Web data browsing/editing where users can easily create and update their data elements that are associated with other data elements, and proposes a table editor for joined views of Web services. With our editor, the user can join multiple Web services, and edit the left/right elements on the joined view in a tabular grid. To support easy manipulation of associated data during the modification, our editor continuously provides the renewed view reflecting the modification. The user can also try out multiple modifications while checking their impact on the view, and decide later whether to commit the modifications to the Web data stores or to discard the modifications. This paper presents some illustrations that demonstrate the use of this joined view editor, discusses the design, and briefly describes its implementation. [ABSTRACT FROM PUBLISHER]

Conventional distributed system courses follow a syllabus in which a list of topics is discussed independently and at different levels of abstractions. We propose to use a wireless sensor network environment to pin all topics down to concrete applications and to maintain issues such as fault tolerance and coordination continuously present. We describe a syllabus with eight conceptual modules, each of them associated to a hands-on experience with wireless sensor networks, which may be assigned either as homework or as a hands-on class, depending on the number of classroom hours that are available. [ABSTRACT FROM PUBLISHER]

In this paper we propose a parallel programming model that combines two well-known execution models: Single Instruction, Multiple Data (SIMD) and Single Program, Multiple Data (SPMD). The combined model supports SIMD-style data parallelism in global address space and supports SPMD-style task parallelism in local address space. One of the most important features in the combined model is that data communication is expressed by global data assignments instead of message passing. We implement this combined programming model into Python, making parallel programming with Python both highly productive and performing on distributed memory multi-core systems. We base the SIMD data parallelism on DistNumPy, an auto-parallel zing version of the Numerical Python (NumPy) package that allows sequential NumPy programs to run on distributed memory architectures. We implement the SPMD task parallelism as an extension to DistNumPy that enables each process to have direct access to the local part of a shared array. To harvest the multi-core benefits in modern processors we exploit multi-threading in both SIMD and SPMD execution models. The multi-threading is completely transparent to the user -- it is implemented in the runtime with Open MP and by using multi-threaded libraries when available. We evaluate the implementation of the combined programming model with several scientific computing benchmarks using two representative multi-core distributed memory systems -- an Intel Nehalem cluster with Infini band interconnects and a Cray XE-6 supercomputer -- up to 1536 cores. The benchmarking results demonstrate scalable good performance. [ABSTRACT FROM PUBLISHER]

Chapel is a parallel programming language designed to improve the productivity and ease of use of conventional and parallel computers. This language currently delivers sub optimal performance when executing codes that perform global data re-allocation operations on distributed memory architectures. This is mainly due to data communication that is done without aggregation (one message for each remote array element). In this work, we analyze Chapel's standard Block and Cyclic distribution modules and optimize the communication routines for array assignments by performing aggregation. Thanks to the expressive power of Chapel, the compiler and runtime have enough information to do communication aggregation without user intervention. The runtime relies on the low-level GAS Net networking layer, whose versions of one-sided bulk put/get routines that support strides are particularly useful for us. Experimental results conducted on Hector (a Cray XE6) and Jaguar (Cray XK6)reveal that the implemented techniques can lead to significant reductions in communication time. [ABSTRACT FROM PUBLISHER]

The rising popularity of graphics processing units is bringing renewed interest in code optimization techniques for SIMD processors. Many of these optimizations rely on divergence analyses, which classify variables as uniform, if they have the same value on every thread, or divergent, if they might not. This paper introduces a new kind of divergence analysis, that is able to represent variables as affine functions of thread identifiers. We have implemented this analysis in Ocelot, an open source compiler, and use it to analyze a suite of 177 CUDA kernels from well-known benchmarks. We can mark about one fourth of all program variables as affine functions of thread identifiers. In addition to the novel divergence analysis, we also introduce the notion of a divergence aware register allocator. This allocator uses information from our analysis to either rematerialize affine variables, or to move uniform variables to shared memory. As a testimony of its effectiveness, our divergence aware allocator produces GPU code that is 29.70% faster than the code produced by Ocelot's register allocator. Divergence analysis with affine constraints is publicly available in the Ocelot compiler since June/2012. [ABSTRACT FROM PUBLISHER]

Localization in previously unknown and GPS-denied areas is challenging, especially, when no infrastructure can be assumed. In this paper, we present a hybrid person localization approach for ad-hoc scenarios. Example applications are search and rescue operations, but also on construction sites or during maintenance tasks of large industrial plants. The outlined scheme is based on received signal strength localization in a wireless sensor network (WSN) and data fusion of inertial sensors. However, the complexity of such systems poses a challenge to non-technicians to operate them. To improve operability, the model-based design principle has been a rigorous change to systems design methodology. In this paper, we adopt the strengths of model-based methods to a heterogeneous distributed and networked system. The advantage of our approach is that the same model-based design environment is later used for control and monitoring of the network in the actual deployment. This allows easy reconfiguration of parameters during an operation. We present some localization results and highlight advantages and experiences gained from our evaluations. We conclude that model-based development on one hand and also model-based runtime control on the other hand are important aspects for future WSN deployments. [ABSTRACT FROM PUBLISHER]

Service Oriented Computing enables distributed applications that orchestrate existing services exported by remote providers. This paradigm requires to explicitly handle possible changes that may affect the orchestration. They include changes that impact its functional behavior (e.g., services being retired by their providers), but also changes in the non-functional behavior of the orchestrated services (e.g., an increased execution time). In the past we developed DSOL: it combines a declarative language to model the orchestration with planning mechanisms to decide at run-time the best flow of actions. In this paper we extend DSOL to support QoS attributes and requirements. In particular, we combine the DSOL planning techniques with a linear optimizer to calculate the optimal plan w.r.t. the QoS requirements. Moreover, we leverage the DSOL ability to adapt the orchestration flow at run-time, to further optimize the QoS perceived by the end users depending on the actual situations encountered. [ABSTRACT FROM PUBLISHER]

Ptides, a programming model for distributed real-time embedded systems, was proposed previously. In this work, we focus on a work flow that applies Ptides in a single-CPU environment using model-based design techniques. Our work flow starts with a programming environment where a real-time application is expressed as a Ptides model. The model captures both the functionality of the system and the desired timing of interactions with the environment. The Ptides simulator supports simulation of both of these aspects. Once the designer is satisfied with the design, a code generator can be used to glue together the application code with a real-time operating system called PtidyOS. To ensure the responsiveness of the real-time program, PtidyOS's scheduler combines Ptides semantics with the earliest-deadline-first policy. To minimize scheduling overhead associated with context switching, PtidyOS uses a single stack for event scheduling and execution, while still enabling event preemptions. We demonstrate the Ptides work flow through a motion control application. The automatically generated code running on PtidyOS is compared with a manual C implementation running on bare silicon. We discuss the trade offs in functionality and performance between these two implementations. [ABSTRACT FROM PUBLISHER]

Wireless Sensor Network (WSN) deployment experiences show that collected data is prone to be faulty. Faults are due to internal and external influences, such as calibration, low battery, environmental interference and sensor aging. However, only few solutions exist to deal with faulty sensory data in WSN. We develop a statistical approach to detect and identify faults in a WSN. In particular, we focus on the identification and classification of data and system fault types as it is essential to perform accurate recovery actions. Our method uses Hidden Markov Models (HMMs) to capture the fault-free dynamics of an environment and dynamics of faulty data. It then performs a structural analysis of these HMMs to determine the type of data and system faults affecting sensor measurements. The approach is validated using real data obtained from over one month of samples from motes deployed in an actual living lab. [ABSTRACT FROM PUBLISHER]

The parallel nature of the multi-core architectural design can only be fully exploited by concurrent applications. This status quo pushed productivity to the forefront of the language design concerns. The community is demanding for new solutions in the design, compilation, and implementation of concurrent languages, making this research area one of great importance and impact. To that extent this paper proposes the expression of data parallelism at subroutine level. The calling of a subroutine in this context spawns several execution flows, each operating on distinct partitions of the input dataset. Such computations can be expressed by simply annotating sequential subroutines with data distribution and reduction policies, delegating the management of the parallel execution to a dedicated runtime system. The paper overviews the key concepts of the model, illustrating them with some small programming examples, and describes a Java implementation built on top of the X10 runtime system. A performance evaluation attests that this approach can provide good performance gains without burdening the programmer with the writing of specialized code. [ABSTRACT FROM PUBLISHER]

Both sensor coverage maximization and energy cost minimization are the fundamental requirements in the design of real-life mobile sensing applications, e.g., (1) deploying environmental sensors (like CO2, fine particle measurement) on public transports to monitor air pollution, (2) analyzing smart phone embedded sensors (like GPS, accelerometer) to recognize people daily activities. However sensor coverage and energy cost contradict each other: the higher frequency mobile sensing takes, the more energy is used, and vise versa. In this paper, we design a novel two-step mobile sensing process ("OptiMoS") to achieve optimal mobile sensing that can effectively balance sensor coverage and energy cost. In the first step, OptiMoS divides the continuous mobile sensor readings into several segments, where the readings in one segment are highly-correlated rather than readings amongst different segments. In the second step, OptiMoS identifies optimal sampling for the sensor readings in each segment, where the selected readings can guarantee reasonably high sensor coverage with limited sampling rate. Various greedy & near-optimal segmentation and sampling methods are designed in OptiMoS, and are evaluated using real-life environmental data from mobile sensors. [ABSTRACT FROM PUBLISHER]

Sensor nodes are generally resource-constrained and MMUs are not present on sensor nodes. Without MMU, operating system is volatile to user program errors. so it is notoriously difficult to write robust programs. In this paper, we present memory safety schemes for sensor programs written in C programming language to isolate user program memory from operating system memory. Our memory safety schemes have shown a number of superiorities over other existing safety schemes for sensor nodes. Evaluations show the overhead of our memory safety schemes and the performance of memory safety is compared with other safety schemes. [ABSTRACT FROM PUBLISHER]

Creating and managing applications for Wireless Sensor Networks (WSNs) is complicated by large scale, resource constraints and network dynamics. Reconfigurable component models minimize these complexities throughout the application lifecycle. However, contemporary component based middleware for WSNs is limited by its poor support for distribution. This paper introduces the Loosely-coupled Component Infrastructure (LooCI), a middleware for building distributed component-based WSN applications. LooCI advances the state-of-the-art by cleanly separating distributed concerns from component implementation, supporting application-level interoperability between heterogeneous WSN platforms and providing compatibility testing of bindings at runtime. Together, these features promote the safe and efficient composition and reconfiguration of distributed WSN applications. We evaluate the performance of LooCI on three classes of sensor nodes and demonstrate that these features can be provided with minimal overhead in terms of computation, memory and message passing. [ABSTRACT FROM PUBLISHER]

We present the concept, design, and implementation of the proxy mote, a Linux-based TinyOS platform able to execute a TinyOS application in a fully functional way. The main use case for the proxy mote is to expose a non-TinyOS (âlegacyâ) sensor/actuator device to TinyOS applications. This is achieved by complementing the proxy mote with a device-specific driver. Multiple proxy motes, each representing its own device, run in parallel on a single PC and communicate among themselves. Thus a distributed, multi-node TinyOS application can use a complex, heterogeneous legacy sensor/actuator installation. At runtime, a proxy mote is a Linux process. Multiple proxy motes form an intra-PC ânetworkâ and exchange Active Message packets over a dedicated infrastructural Linux process that acts as a switch. We include performance results for the proxy mote and proxy network, for typical TinyOS applications. The results demonstrate the feasibility of the approach. [ABSTRACT FROM PUBLISHER]

Wireless Sensor Networks are used in a large number of tracking and monitoring applications. The level of security required by an application depends on the threat level, available resources, and security requirements. In this paper, we present a modular and extensible framework, called Adaptive Security Framework (ASF) that adjusts security to the detected threats, available energy and memory, and application requirements. The framework includes three types of components: the Context modules, the Security Adaptation module, and the Security layer. The security level is modified according to the output of the Context modules, and it is then used to enable the appropriate security primitives available in the Security layer. We evaluate our solution in multiple attack scenarios, we determine its resource consumption and we compare it to other State of the Art solutions. Our framework has the following advantages: it takes into consideration the context, but also allows for manual reconfiguration, it has a global, aggregated view of the context, it provides different authentication and encryption algorithms associated to each security level, it is extensible and modular. [ABSTRACT FROM PUBLISHER]

Multi-Owner Wireless Sensor Networks consist of devices owned by different entities. They have the purpose of covering large areas and reducing energy consumption associated with transmission over long distances. We propose the use of Virtual Networks with the purpose of grouping resources in a Multi-Owner Wireless Sensor Network and delivering a service to the associated owner. We designed a scheme for securing communication in a Virtual Network. The nodes that belong to a specific owner must authenticate themselves before receiving the Virtual Network credentials and the Service Description. We investigated the impact of false data injection and eavesdropping attacks generated by external or internal compromised nodes. We conclude that our security scheme minimizes the impact of attacks against Multi-Owner Wireless Sensor Networks, while allowing data aggregation for efficiency purposes. [ABSTRACT FROM PUBLISHER]

Wireless sensor networks consist of spatially distributed sensor to monitor physical or environmental conditions and cooperatively pass their data to a central location. These kinds of network have come into prominence because they hold the potential to revolutionize many segments of our life from environmental monitoring and conservation to automation in traffic monitoring and health-care business. This paper focus on design, implementation and operation of a sensor network requires the assemblage of various disciplines including embedded systems, hardware, networking, information management and distributed algorithms. Most applications of WSNs require deployment in unattended remote locations. Therefore, power awareness is fundamental to data dissemination and routing in a WSN. [ABSTRACT FROM PUBLISHER]

The vantage points of routers along end-to-end paths in the Internet have long made them a compelling target for additional functionality. In this paper, we describe a new method for router data plane programmability that is simple, general, flexible and safe and enables complex network services to be built and deployed. Our method targets network processor (NP)- and FPGA-based routers, and is based on two central ideas: (1) primitive functions for routers that are designed for specific target service domains, and (2) a primitive-aware programming language that is expressive, easy to use and easy to analyze. To demonstrate our method, we describe a set of primitive functions in the context of three diverse domains — network measurement, real-time applications and traffic engineering. Next, we describe Morpheme, our primitive-aware programming language, and show how it can be statically analyzed to safeguard router processor and memory resources. We demonstrate the efficacy of our method by implementing the primitive functions in the Click modular router [1] and a prototype Morpheme compiler. Through a series of microbenchmark experiments, we substantiate the capabilities of our prototype implementation. [ABSTRACT FROM PUBLISHER]