We propose a technique to protect digital images using the content-associated copyright messages generated by combining the original copyright message with the gradient of intensity of digital images The proposed technique enables the distribution of the original copyright message without any distortion of original digital images by avoiding embedment of the original copyright message into images In addition to the efficiency of generating copyright messages, it also has a relatively low computational complexity To verify the propriety of the proposed technique, we performed experiments on its robustness to the external attacks such as histogram equalization, median filtering, rotation, and cropping Experimental results on restoring the copyright message from images distorted by attacks show that more than 90%, on the average, can be recovered

A Novel Copyright Protection for Digital Images Using the Gradient of Image Intensity

Wireless sensor networks promise a new paradigm for gathering data via collaboration among sensors spreading over a large geometrical region. Many applications impose delay requirements for data gathering and ask for time-efficient schedules for aggregating sensed data and sending to the data sink. In this paper, the authors study the minimum data aggregation time problem under collision-free transmission model. In each time round, data sent by a sensor reaches all sensors within its transmission range, but a sensor can receive data only when it is the only data that reaches the sensor. The goal is to find the method that schedules data transmission and aggregation at sensors so that the time for all requested data to be sent to the data sink is minimal. The authors propose a new approximation algorithm for this NP-hard problem with guaranteed performance ratio $$\frac{{7\Delta }}{{\log _{2} {\left| {\text{S}} \right|}}} + c$$
 , which significantly reduces the current best ratio of Δ 1, where S is the set of sensors containing source data, Δ is the maximal number of sensors within the transmission range of any sensor, and c is a constant. The authors also conduct extensive simulation, the obtained results justify the improvement of proposed algorithm over the existing one.

Improved Algorithm for Minimum Data Aggregation Time Problem in Wireless Sensor Networks

In this paper, we use an integrated architecture that takes advantage of the low cost mobile sensor networks and 3G cellular networks to accommodate multimedia medical calls with differentiated Quality-of-Service (QoS) requirements. We propose a low-energy, distributed, and concentric-zone-based data query mechanism that takes advantages of hierarchical ad hoc routing algorithms to enable a medical specialist to collect physiological data from mobile and/or remote patients. The medical specialist uses cellular network to report patients' data to the medical center. Moreover, we propose a transmission scheme among different zones with balance-based energy efficiency, which can extend network lifetime. We evaluate the validity of our proposals through simulations and analyze their performance. Our results clearly indicate the energy efficiency of the proposed sensor network query algorithms and the efficiency of our multiclass medical call admission control scheme in terms of meeting the multimedia telemedicine QoS requirements.

Mobile telemedicine sensor networks with low-energy data query and network lifetime considerations

In many-to-one wireless sensor networks, there exists an unbalanced power consumption problem; that is, nodes near the data sink or base station, called hot spots, have a high probability of forwarding a high amount of packets and die early. Most of previous work is dedicated to constructing a long-lived aggregation tree, while leaving the hot spot problem unsolved. When the locations of sinks are given and thus fixed, this work attempts to alleviate the hot spot problem by exploiting techniques to balance power consumption for nodes in the tree by switching multiple fixed sinks. The first balancing technique is called manipulating multiple long-lived trees (MMLT), which constructs multiple long-lived data aggregation trees for multiple sinks, and cyclically switches a data aggregation tree to another, after a sink collects information for a predefined period of time. To reduce overhead, we further propose another technique which constructs only a single tree and shares it with all sink nodes. To evaluate the performance of these two balancing techniques, we run simulations with various setup environments and compare them with the balanced tree method.

Activating the Hot Spot Problem by Switching Multiple Sinks in Wireless Sensor Networks

Energy is a scarce resource in wireless networks. Network coding has been proposed recently as a means to reduce the number of transmissions and energy consumption. In this paper, we introduce timing control into network coding to further enhance its performance. It is found that when bandwidth is sufficient, the extra delay introduced by waiting for additional data to perform network coding will increase the number of codings without affecting system throughput. Both delay and throughput suffers when bandwidth is insufficient. An adaptive energy-efficient timing control algorithm called AEETC is proposed which can automatically adjust local node's transmission behavior on the basis of the network traffic conditions. Simulation results demonstrate that AEETC increases network coding by 7% to 60% for light network load and is able to provide good performance in terms of delay, throughput and the number of successful codings.

AEETC--adaptive energy-efficient timing control in wireless networks with network coding

Data aggregation in Wireless Sensor Networks (WSNs) has attracted wide attention since it could reduce the amount of wireless data communication and thus save power consumption, which is one of the top concerns in low-power WSN systems. Given a Data Aggregation Tree (DAT) for data query purpose in a WSN, and the expected query accuracy, we show the feasibility to use a low-cost timing control scheme to adaptively adjust the waiting period in each DAT level so that the end-to-end query delay could be optimized, i.e. without unnecessary pause in an aggregation node. For such an adaptive timing control scheme, we propose to use a Finite State Machine (FSM)- based auto-feedback control algorithm to adjust the waiting period of each DAT node to "timely" respond to the queries. Our sensor network simulation results and hardware experiments verify the validity of our proposed timing control scheme.

C. May

Papers

Data Aggregation in Distributed Sensor Networks: Towards An Adaptive Timing Control