By applying a simple shortest/minimum-cost routing algorithm, the mobile ad-hoc network (MANET) with heavy data transmissions may be easily congested if multiple routes meet at the same relay node. Therefore, those busy nodes should be avoided when a new path is established. The task of optimal path seeking becomes more challenging when a MANET is equipped with directional antennas that may cause directional interference with neighboring receivers. The motivation of our research is to build an intelligent proactive routing scheme for MANETs with directional antennas. Our directional routing protocol considers not only the global traffic distribution in different areas of the MANET, but also the properties of directional antennas. It uses a spatio-temporal deep learning algorithm to predict the next-time snapshot of a directional heat map (DHM), which shows the traffic density distribution in each network location as well as the coverage of each directional antenna. The DHM is then used to identify the optimal path that can avoid congested areas as well as the interference from all neighboring directional links. Furthermore, an optimization algorithm is designed to perform optimal path selection. It splits a single path into multiple paths converge later on into one path, if the path needs to go around a congested area. Therefore, our routing scheme achieves better quality-of-service (QoS) performance than existing routing schemes.

UAV networks consisting of reduced size, weight, and power (low SWaP) fixed-wing UAVs are used for various applications such as search and rescue, surveillance, and tracking. To carry out these operations efficiently, there is a need to develop scalable, decentralized autonomous UAV network architectures with high network connectivity. However, the area coverage and the network connectivity requirements exhibit a trade-off. In this paper, a connectivity-aware pheromone mobility (CAP) model is designed for search and rescue operations, which is capable of maintaining connectivity among UAVs in the network. We use stigmergy-based digital pheromone maps along with distance-based local connectivity information to autonomously coordinate the UAV movements, in order to improve its map coverage efficiency while maintaining high network connectivity.

A node equipped with a multi-beam antenna can achieve a throughput of up to$m$times as compared to a single-beam antenna, by simultaneously communicating on its$m$non-interfering beams. However, the existing multi-beam medium access control (MAC) schemes can achieve concurrent data communication only when the transmitter nodes are locally synchronized. Asynchronous packet arrival at a multi-beam receiver node would increase the node deafness and MAC-layer capture problems, and thereby limit the data throughput. This paper presents an asynchronous multi-beam MAC protocol for multi-hop wireless networks, which makes the following enhancements to the existing multi-beam MAC schemes (i) A windowing mechanism to achieve concurrent communication when the packet arrival is asynchronous, (ii) A smart packet processing mechanism which reduces the node deafness, hidden terminals and MAC-layer capture problems, and (iii) A channel access mechanism which decreases resource wastage and node starvation. Our proposed protocol also works in the networks that deploy the nodes equipped with single-beam as well as multi-beam antennas. Simulation results demonstrate a superior performance of our proposed protocol.

A low-cap power budget is challenging for exascale computing. Dynamic Voltage and Frequency Scaling (DVFS) and Uncore Frequency Scaling (UFS) are the two widely used techniques for limiting the HPC application's energy footprint. However, existing approaches fail to provide a unified solution that can work with different types of parallel programming models and applications.

The emergence of multi-beam directional antennas (MBDAs) has paved the way for fast and high-throughput data communications by providing concurrent multi-directional transmissions. However, the existing routing protocols are not capable of utilizing the advantages of MBDAs. In this paper, we have developed a new routing scheme, called volcano routing, which can exploit the concurrent packet dispatching capability of MBDAs for high-throughput data delivery. Its topology resembles the flow of volcano lava and several routing “pipes” are used, which can detour around the network “holes” or blocked areas. The routing process consists of two phases: 1) Main path search phase: There is a main path at the core of each pipe. Multiple optimal main paths are formed that have a high potential of adding side nodes to enable multi-beam communications. A hierarchical scoring system and the performance metrics are used to evaluate the quality of the main paths. 2) Volcano establishment phase: The top-quality main paths are selected, and side paths are formed around each main path to establish the volcano pipes. A multi-beam traffic scheduling and dispatching policy is also proposed to achieve better performance. Our results show that the volcano routing scheme can exploit the advantages of MBDAs for achieving high data rates.

A set of novel routing protocols is proposed for directional hierarchical airborne networks. These networks use a two-level architecture, where the higher-level network is sparse with directional long-distance links that support the high data-rate communication. The lower-level network consists of high-density nodes with short-distance and low data-rate links. We assume that the higher-level nodes are equipped with multi-beam antennas, whereas the lower-level nodes have omni-directional antennas. We use the bio-inspired algorithms (based on moth and ant behaviors) to design the routing schemes for both levels. Specifically, we use the male moth's light source pursuing pattern for routing the data from an event node to the highly mobile sink in lower-level network, and the ant's chemical trail maintenance principle to trace the trajectory of commander node to deliver the data from lower-level node to the commander node in the higher-level network, with minimum delay. In addition, we construct a weighted fence routing topology among higher-level nodes with multi-beam antennas, in order to achieve high throughput. Our simulation results demonstrate that significant performance improvement is achieved by the bio-inspired routing schemes, compared with conventional ad hoc routing schemes.

This paper presents an intelligent spectrum mobility management scheme for cognitive radio networks. The spectrum mobility could involve spectrum handoff (i.e., the user switches to a new channel) or stay-and-wait (i.e., the user pauses the transmission for a while until the channel quality improves again). An optimal spectrum mobility management scheme needs to consider its long-term impact on the network performance, such as throughput and delay, instead of optimizing only the short-term performance. We use a machine learning scheme, called the Transfer Actor-Critic Learning (TACT), for the spectrum mobility management. The proposed scheme uses a comprehensive reward function that considers the channel utilization factor (CUF), packet error rate (PER), packet dropping rate (PDR), and flow throughput. Here, the CUF is determined by the spectrum sensing accuracy and channel holding time. The PDR is calculated from the non-preemptive M/G/1 queueing model, and the flow throughput is estimated from a link-adaptive transmission scheme, which utilizes the rateless (Raptor) codes. The proposed scheme achieves a higher reward, in terms of the mean opinion score, compared to the myopic and Q-learning based spectrum management schemes.

We propose a novel spectrum decision scheme (i.e., channel selection and handoff) for wireless mesh networks (WMN) which use multiple channels and nodes equipped with multi-beam directional antennas. Our scheme has the following features: (i) It performs spectrum decision by considering various WMN parameters, including the channel quality, beam orientation, antenna-caused deafness and capture effects, and application priority level. (ii) It uses the reinforcement learning (RL)-based spectrum decision process to achieve the optimal quality of multimedia transmission in the long term. However, a newly-joined WMN node could take a long time to make a correct spectrum decision due to the difficult choice of initial RL parameters. Therefore, our scheme uses the apprenticeship learning in conjunction with the RL model, to speed up the spectrum decision process by choosing a suitable neighboring node (called “expert”) to teach a newly-joined node (called “apprentice”). Our experiments demonstrate that the proposed spectrum decision scheme improves the network performance and multimedia transmission quality.

In this paper, we propose the concept of "channel+ beam" handoff (CBH) in cognitive radio networks (CRNs) with multi-beam smart antennas (MBSAs). We address the multi-class spectrum handoff issue, based on the user priority, by using the mixed Preemptive/Non-Preemptive M/G/1 queueing model with discretion rule. The discretion rule sets the threshold for the preemption of the low-priority secondary users (SUs) based on the remaining service time. Since each beam of the MBSA can use a different CRN channel, we design a delay-constrained CBH scheme in which the packets in the interrupted beam can be detoured through neighboring beams. The probability of beam handoff is determined based on their channel capacity and buffer fullness of the queue associated with the neighboring beams. By using the CBH model with discretion rule, a low priority SU can escape from multiple interruptions during the completion of its service. Our simulation results show that the mixed queueing model with discretion rule reduces the queueing delay (i.e., handoff delay) of the high priority SUs, and the packet detouring scheme gives fair spectrum access opportunities to the low priority SUs.

Conventional wireless mesh network (WMN)routing protocols are designed for the nodes that use the omni-directional or single-beam directional antennas. This research presents a throughput-efficient routing scheme for WMN, by taking advantage of the nodes equipped with the multi-beam directional antennas (MBDAs). Our routing design has the following two novel features: First, it is a cross-layer design by integrating the routing scheme with multi-beam oriented medium access control (MAC) scheme. Second, the routing topology has a diamond-like shape and uses the multi-path routes (i.e., one main path and a few side paths). The diamond shape makes the traffic converge and diverge periodically in the routing paths, which exploits the simultaneous data delivery capability of multi-beam antennas, and enhances the network throughput. Our simulation results demonstrate the high throughput efficiency of the proposed multi-beam routing scheme.

We present a real-time, priority-aware joint packet fragmentation and error protection scheme for transmitting H.264/AVC compressed video over Rayleigh fading channels. A priority is assigned to every video slice based on the predicted cumulative mean squared error (CMSE) contributed by its loss relative to all the slices of the group of pictures (GOP). Here, the CMSE of a slice, which is predicted by using our low-complexity generalized linear model, represents the degradation in video quality contributed by its loss. The slices of a frame belonging to the same priority are aggregated to form video packet(s). We simulate the fragment error rates (FERs) for a combination of different fragment sizes and rate compatible punctured convolutional (RCPC) code rates. These FERs are then used to determine the optimal fragment sizes and code rates for packets of each priority class by minimizing the expected normalized predicted CMSE of all the priority classes per GOP in H.264 video bitstream. We observed a significant improvement in the received video quality over the conventional and priority-agnostic packet fragmentation schemes.

Enabling the spectrum handoff for multimedia applications in cognitive radio networks (CRNs) is challenging, due to multiple interruptions from primary users (PUs), contentions among secondary users (SUs), and heterogenous Quality-of-Experience (QoE) requirements. In this paper, we propose a learning-based and QoE-driven spectrum handoff scheme to maximize the multimedia users' satisfaction. We develop a mixed preemptive and non-preemptive resume priority (PRP/NPRP) M/G/1 queueing model for modeling the spectrum usage behavior for prioritized multimedia applications. Then, a mathematical framework is formulated to analyze the performance of SUs. We apply the reinforcement learning to our QoE-driven spectrum handoff scheme to maximize the quality of video transmissions in the long term. The proposed learning scheme is asymptotically optimal, model-free, and can adaptively perform spectrum handoff for the changing channel conditions and traffic load. Experimental results demonstrate the effectiveness of the proposed queueing model for prioritized traffic in CRNs, and show that the proposed learning-based QoE-driven spectrum handoff scheme improves quality of video transmissions.

The unequal error protection (UEP) has shown promising results for transmitting video over error-prone wireless channels. In this paper, we investigate the cross-layer design of forward error correction (FEC) schemes by using the UEP Raptor codes at the application layer (AL) and UEP rate compatible punctured convolutional (RCPC) codes at physical layer (PHY) for prioritized video packets. The video packets are prioritized based on their contribution to the received video quality. A genetic algorithm (GA)-based optimization algorithm is proposed to find the optimal parameters for both Raptor and RCPC codes, to minimize the video distortion and maximize the peak signal-to-noise-ratio for the given video bit rates and channel constraints (i.e., SNR and available bandwidth). We evaluate the performance of four combinations of the UEP schemes for H.264/AVC encoded video sequences over the AWGN and Rayleigh fading channels and show the superiority of the optimized cross-layer UEP FEC scheme. For Rayleigh fading channel, the proposed cross-layer optimization uses two different time-scales at AL and PHY which allows PHY to adapt faster to the changing channel quality.

Cognitive Radio (CR) can efficiently utilize the licensed wideband spectrum whenever the primary users (PUs) are absent. Spectrum sensing is the first step and an important function to fulfill the CR system. A cyclostationary feature detector can robustly detect the PU's modulated signals even under strong interferences. However this detector needs high signal sampling rate and also puts heavy computation burden on the system. Compressive sensing (CS) can compress the data at the front sampling end but has high overload and delay from the reconstruction side. In this work we generate the compressive CR spectrum measurement by utilizing both the cyclostationary feature and sparsity prior knowledge at the spectrum sensing front end, and we apply the compressive signal processing (CSP) without the need of signal or feature reconstruction. This can significantly shorten the CR spectrum sensing time. Our experimental results have shown the pattern analysis accuracy and efficiency of our CSP scheme.

The quality of H.264/AVC compressed video delivery over wireless channels is affected by packet losses. Aggregating H.264/AVC slices to form video packets with sizes adaptive to their importance can improve transmission reliability. Larger packets are more likely to be in error but smaller packets cause more overhead. A second method is assigning stronger channel code rates to more important slices. We use cross-layer dynamic programming to address both adaptive packet formation as well as RCPC-channel code rate allocation simultaneously, to improve received video quality. Simulation results show the advantages of the proposed scheme.

We propose a low complexity Generalized Linear Model (GLM) for prioritizing slices during real-time H.264/AVC compressed video streaming. We train the GLM over a video database to predict the Cumulative Mean Square Error (CMSE) corresponding to individual slice losses by using a combination of efficient video parameters which can be easily extracted during the encoding of a frame. We prioritize the slices generated within a Group of Pictures (GOP) based on the predicted CMSE by using a Quartile Based Prioritization (QBP) scheme. For comparison, we also perform QBP on measured CMSE values from individual pre-encoded slice losses and analyze the priority misclassifications of the slices. We validate our model by applying Unequal Error Protection (UEP) using RCPC codes to the different prioritized bitstreams and evaluating their performance over noisy channels. Simulation results show that predicted CMSE schemes achieve PSNR performance close to that of the measured CMSE schemes for different slice sizes, video bitrates and over different channel SNRs.

We introduce a cross-layer priority-aware packet fragmentation scheme at the MAC layer to enhance the quality of pre-encoded H.264/AVC compressed bitstreams over bit-rate limited error-prone links in wireless networks. The H.264 slices are classified in four priorities at the encoder based on their cumulative mean square error (CMSE) contribution towards the received video quality. The slices of a priority class in each frame are aggregated into video packets of corresponding priority. We derive the optimal fragment size for each priority class which achieves the maximum expected weighted goodput at different encoded video bit rates, slice sizes and bit error rates. Priority-aware packet fragmentation invokes slice discard in the buffer due to channel bit rate constraints on allocating fragment header bits. We propose a slice discard scheme using frame importance and slice CMSE contribution to control error propagation effects. Packet fragmentation is extended to slice fragmentation by modifying the conventional H.264 decoder to handle partial slice decoding. Priority-aware slice fragmentation combined with the proposed slice discard scheme provides considerable PSNR and VQM gains as compared to priority-agnostic fragmentation.

We introduce a cross-layer priority-aware packet fragmentation scheme to enhance the quality of H.264 compressed bitstreams over bit-rate limited error-prone links in packet networks. The H.264 slices are prioritized in the encoder based on their cumulative mean square error (CMSE) contribution towards the received video quality. Specifically we derive the optimal fragment size for each priority level which achieves the maximum expected weighted goodput at different encoded video bit rates and slice sizes. The packet fragmentation scheme uses slice discard in the buffer. Simulation results show that the proposed scheme provides considerably improved video quality.

Recently, multimedia transmission over cognitive radio networks (CRNs) becomes an important topic due to the CR's capability of using unoccupied spectrum for data transmission. Conventional work has focused on typical quality-of-service (QoS) factors such as radio link reliability, maximum tolerable communication delay, and spectral efficiency. However, there is no work considering the impact of CR spectrum sensing frequency and packet-loading scheme on multimedia QoS. Here the spectrum sensing frequency means how frequently a CR user detects the free spectrum. Continuous, frequent spectrum sensing could increase the medium access control (MAC) layer processing overhead and delay, and cause some multimedia packets to miss the receiving deadline, and thus decrease the multimedia quality at the receiver side. In this research, we will derive the math model between the spectrum sensing frequency and the number of remaining packets that need to be sent, as well as the relationship between spectrum sensing frequency and the new channel availability time during which the CRN user is allowed to use a new channel (after the current channel is re-occupied by primary users) to continue packet transmission. A smaller number of remaining packets and a larger value of new channel availability time will help to transmit multimedia packets within a delay deadline. Based on the above relationship model, we select appropriate spectrum sensing frequency under single-channel case, and study the trade-offs among the number of selected channels, optimal spectrum sensing frequency, and packet-loading scheme under multi-channel case. The optimal spectrum sensing frequency and packet-loading solutions for multi-channel case are obtained by using the combination of Hughes-Hartogs and discrete particle swarm optimization (DPSO) algorithms. Our experiments of JPEG2000 packet-stream and H.264 video packet-stream transmission over CRN demonstrate the validity of our spectrum sensing frequency selection and packet-loading scheme.

Compressed video data is very sensitive to channel-induced errors and network losses. Most conventional unequal error protection techniques involve forward error correction codes of different rates or asymmetric signal constellations for data of different priorities. It is yet unknown if combining the above two techniques can further improve performance. In this paper, we investigate rate-compatible punctured convolutional (RCPC) codes concatenated with hierarchical QAM for H.264 encoded video sequences. We investigate system constraints and propose an optimization formulation to compute the optimal parameters of the proposed system under the given source significance information. An upper bound to the bit error rate of the proposed system is derived as a function of system parameters, including the code rate and geometry of the constellation. The example shown demonstrates system design for H.264 video, where PSNR improvement is observed.

Abstract An event‐to‐sink reliable transport (ESRT) control scheme was recently proposed to address the event‐to‐sink reliability issues in wireless sensor network (WSN). In this paper, we study the performance of ESRT in the presence of ‘over‐demanding’ event reliability, using both the analytical and simulation approaches. We show that the ESRT protocol does not achieve optimum reliability and begins to fluctuate between two inefficient network states. With insights from update mechanism in ESRT, we propose a new algorithm, called enhanced ESRT (E2SRT), to solve the ‘over‐demanding’ event reliability problem and to stabilize the network. Simulation results show that E2SRT outperforms ESRT in terms of both reliability and energy consumption in the presence of ‘over‐demanding’ event reliability. Besides, it ensures robust convergence in the presence of dynamic network environments. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract Underwater Acoustic Networks (UANs) have important applications in ocean exploration and lake pollution monitoring. UANs are however different from terrestrial sensor networks due to their highly variable, long propagation delay, and mobility. Clock synchronization is an important protocol to achieve timing‐based sensor communications. In this paper, we propose a three dimensional, scalable UAN time synchronization scheme that can achieve both horizontal (i.e., in the same water depth) and vertical (i.e., from bottom up to the surface) clock synchronization to overcome the effects of long acoustic delay. To secure UAN clock synchronization services, we also propose a two‐step security UAN synchronization model: (1) correlation test and (2) statistical reputation and trust model. The proposed model can detect outlier timestamp data and identify nodes generating insider attacks. Copyright © 2007 John Wiley & Sons, Ltd.

Cardiovascular diseases are the single largest cause of morbidity and mortality in the U.S. and Western world. Tele- cardiology through RFID-based wireless sensor networks can provide anytime cardiac patient monitoring in large nursing homes. Wireless medical sensors and PDA devices can provide continuous transmission of patients' cardiac data (such as ECG, blood pressure, SpO2, etc.). However, the radio broadcasting nature has the risk of losing confidentiality (i.e. privacy) of patients' data. This paper discusses our research on a secure RFID/sensor based tele-cardiology system. It is based on the light-weight encryption and key management algorithms. The RFID helps trace the mobility of patients and manage medical facilities in nursing homes.

Our research aims to address the challenging trustworthiness issues in wireless sensor and actuator networks (WSANs). As trustworthiness requires data to be transmitted among actuators and sensors with desired 'reliability' and 'security', we propose a low-complexity transmission reliability scheme that is based on local wireless path repair and hop-to-hop retransmission. Since WSANs have specific network constraints and data transmission requirements compared to general ad hoc networks and other wireless/wired networks, the security issues need to be tackled accordingly. We propose to seamlessly integrate WASN security with a promising routing architecture that is scalable and energy-efficient. In this paper, we also develop two-level re-keying/re-routing schemes that can not only adapt to a dynamic network topology but also securely update keys for each data transmission session.

The data over cable service interface specifications (DOCSIS) of the Multimedia Cable Network System (MCNS) organization intends to support IP traffic over HFC (hybrid fiber/coax) networks with significantly higher data rates than analog modems and integrated service digital network (ISDN) links. The high speed access enables the delivery of high quality audio, video and interactive services. To support quality-of-service (QoS) for such applications, it is important for HFC networks to provide effective medium access and traffic scheduling mechanisms. We consider an HFC network that has a shared upstream channel for transmission from stations assigned with different service priorities to the headend. We first present a multilevel priority collision resolution scheme with adaptive contention window adjustment. This collision resolution scheme separates and resolves collisions for different classes of critically delay-sensitive and best effort traffics, thus achieving the capability of preemptive priorities. To enhance the performance of our scheme, we adopt a novel methodology in which the headend dynamically selects the optimal backoff window size according to the estimate of the number of contending stations for each priority class. A data transmission traffic scheduling policy with multiple priority queues is also employed in the headend. This scheduling strategy is used to satisfy bandwidth requirements of higher priority traffics. A set of simulation scenarios is conducted using OPNET to demonstrate the performance efficiency of the proposed scheme.

A dynamic call admission control and resource reservation scheme suitable for CDMA systems is proposed. Preferential treatment is given to high priority calls by preserving an interference guard margin (IGM), which is dynamically adjusted by referencing traffic conditions in neighboring cells based upon users' quality of service. A comprehensive service model is used including users' service rates, priority levels, mobility and rate adaptivity. Simulations are conducted by OPNET to study the performance in terms of the objective function under different traffic conditions.

A novel scheduling mechanism and a new bandwidth allocation scheme are proposed in this work to support multimedia traffic over DOCSIS (Data Over Cable System Interface Specification)-compliant cable networks. The primary goal of our research is to improve the transmission of real-time variable bit rate (VBR) traffic in terms of throughput and delay under the current DOCSIS specifications. To support integrated services, we also consider the transmission of constant bit rate (CBR) traffic and non-real-time traffic in the simulation. To demonstrate the performance, we compare the result of the proposed scheme with that of a simple multiple priority scheme. It is shown via simulation that the proposed method provides a significant amount of improvement over existing DOCSIS QoS scheduling services.

A dynamic call admission control (CAC) and its associated resource reservation (RR) schemes are proposed in this research based on the guard channel (GC) concept for a wireless cellular system supporting multiple quality of service (QoS) classes. The proposed CAC policy selects the resource access threshold according to the estimated number of incoming call requests of different QoS classes. The amount of resources to be reserved is dynamically adjusted by considering neighboring-cell higher-priority calls, which are likely to handoff. The rationale behind our proposed dynamic CAC and RR scheme is to make an efficient resource reservation for priority calls by considering potential handoff calls in the neighboring cells, based on their signal to noise ratio (SNR) information and the traffic profile for each mobile. A comprehensive service model is developed, which includes not only mobile terminals' bandwidth requirements but also their different levels of priority, rate adaptivity as well as their mobility. Simulations are conducted by OPNET to study the performance of our proposed scheme in terms of cost function and system utilization under different traffic conditions.

Current coding techniques for 3-D graphic models mainly focus on coding efficiency, which makes them extremely sensitive to channel errors due to the irregular mesh structure. We introduce a new approach for error-resilient coding of arbitrary 3-D graphic models by extending the error-free constructive traversal compression scheme proposed by Li and Kuo (see MPEG-4 Tokyo Meeting, 1998, Contribution Doc. M3324, and Proc. IEEE, vol.86, p.1052-63, 1998). A 3-D mesh of an arbitrary structure is partitioned into pieces of a smaller uniform size with joint boundaries. The size of a piece is determined adaptively based on the channel error rate. The topology and geometry information of each joint boundary and each piece of a connected component is coded independently. The coded topology and first several important bit-planes of the joint-boundary data are protected against channel errors by using the Bose-Chaudhuri-Hocquenghem error-correcting code. At the decoder, each piece is decoded and checked for channel errors. The decoded joint-boundary information is used to perform data recovery and error concealment on the corrupted piece data. All decoded pieces are combined together according to their configuration to reconstruct all connected components of the complete 3-D model. Our experiments demonstrate that the proposed approach has excellent error resiliency at a reasonable bit-rate overhead. The techniques is also capable of incrementally rendering one connected component of the 3-D model at a time.

Summary form only given. In order to limit error propagation, we divide the topological data of the entire mesh into several segments. Each segment is identified by its synchronization word and header. Due to the use of the arithmetic coder, data of a whole segment would often become useless in the presence of even a single bit error. Furthermore, several adjacent segments may be corrupted simultaneously at high bit error rates (BER). As a result, a lot of data would be required to be retransmitted in the presence of errors. Retransmitted data may also in turn get corrupted in high BER conditions. This would result in a considerable loss of coding efficiency and increased delay. We propose the use of reversible variable length codes (RVLC) to solve this problem. RVLC not only prevents error propagation in one segment but also efficiently detects the distorted portion of the bitstream due to their capability of two-way decoding. This would allow the recovery of a large portion of data from a corrupted segment. The amount of retransmitted data can thus be drastically reduced. RVLC can be matched to various sources with different probability distributions by adjusting their suffix length, and have been found suitable for image and video coding. However, the application of RVLC to robust 3D mesh coding has not yet been studied. Our study of the suitability of RVLC for the topological data is presented in this research. Experiments have been carried to prove the efficiency of the proposed robust 3D graphic coding algorithm. To design an efficient pre-defined code table, a large set of 300 MPEG-4 selected 3D models have been used in our experiments. The use of predefined code tables would result in a significantly reduced computational complexity.

Current coding techniques for 3D graphic models focus more on coding efficiency, which makes them extremely sensitive to channel errors due to the irregular nature of the mesh structure. In this paper, we propose a robust mesh partitioning scheme which can reduce the error propagation length and allow a piecewise reconstruction of the original mesh while maintaining a high compression ratio. Our method first segments an arbitrary 3D mesh into a set of independent connected components. Each component is further segmented into several independent 3D pieces based on the error rate. Joint boundary information is efficiently coded which will be used to stick segmented pieces together. All resulting pieces are grouped by their sizes to keep each group as a basic unit which has a near equal length, which is determined by the error rate. The data partitioning technique is finally used to keep track of each group of pieces. Errors are thus limited to each group, and can be corrected easily. The proposed technique can also be used in graphic editing, partial texture mapping and other applications.

EBCOT (embedded block coding with optimized truncation) is an efficient image coding technique adopted by JPEG-2000 VM. EBCOT divides each subband into independently coded 64/spl times/64 blocks, and is therefore inherently more robust to errors than many other wavelet-based schemes. However, loss of data in any lower frequency subband block in EBCOT can still damage the image beyond repair. This work discusses the use of reversible variable length codes (RVLC) for the coding of lower frequency subbands in EBCOT, instead of arithmetic codes. It is demonstrated that RVLCs demand a very low bit-rate overhead.

Embedded block coding with optimized truncation (EBCOT) is an efficient and scalable wavelet-based image coding technique, which divides each subband in independently coded blocks. It is therefore more error resilient than many other wavelet based schemes. However, the loss of data of a block in any lower frequency subband in EBCOT can still degrade the perceptual image quality considerably. This paper investigates the use of reversible variable length codes (RVLC) and data partitioning for the coding of coefficients of low frequency subbands in EBCOT (instead of arithmetic codes). RVLCs are known to have a superior error recovery property due to their two-way decoding capability. It is demonstrated that the proposed scheme requires only a small amount of overhead in the bit-rate, but provides a significantly improved performance in the presence of errors.