Smart education has become an important direction of future education, but the improvement and practice of wisdom teaching is a long process. In this paper, we present the available teaching platforms that support wisdom teaching of Jinan University, and carry out teaching implementation, show the effect of the initial exploration of the wisdom teaching of the “Information Technology” course.

This paper analyzes the existing problems in current teaching of programming courses and explores the teaching reform by introducing online-offline blended teaching and assessing model. Taking object-oriented programming course as an example, SPOC is firstly constructed with the help of web-based platform to support online learning of students. Then, the flipped classroom with smart teaching tools is used to enhance the face-to-face interactivity and engagement of students. Thirdly, cooperative course projects are integrated into experimental teaching to enhance the application of programming skills and raise teamwork spirit. Finally, a Process-oriented Comprehensive Assessment model (PCA) based on learning data is developed to optimize the evaluation in traditional face-to-face teaching. The survey and practices have shown that the teaching model can significantly improve the comprehensive ability, innovative thinking and achieve personalized learning results.

针对Matlab Programming课程教学学生人数多且基础不一的问题,基于课程内容繁杂、实践性强的特点,充分利用线上线下混合教学平台,采用翻转课堂和项目式学习结合的分段式教学,介绍分段式教学设计和实施过程并给出教学考核和评价方法.

Based on the concept of the educational Metaverse, this paper combs the theoretical basis, development process and application scenario of the Metaverse. For the course of information technology, the blended teaching practice based on the concept of Metaverse is carried out, including the design of teaching process, the integration of teaching platform, the construction of resources and the setting of evaluation method. We have designed a teaching scheme based on the concept of Metaverse, including the integration of online teaching platform, resource construction and deployment, assessment design and so on. The teaching has been implemented in the advertising major from 2019 to 2021, and it is found that the teaching effect has been significantly improved.

Flooding is a fundamental function for the network-wide dissemination of command, query, and code update in wireless sensor networks. However, it is challenging to enable fast and energy-efficient flooding in sensor networks with low-duty cycles because it is rare that multiple neighboring nodes wake up at the same time, making broadcast instinct of wireless radio unavailable. The unreliability of wireless links deteriorates the situation. In this work, we study the delay-constrained flooding problem in order to disseminate data packets to all nodes within given expected delivery delay. In particular, a transmission power control–based flooding algorithm is proposed to reduce the flooding delay in such low-duty-cycle sensor networks. According to the soft delay bound, each node can locally adjust its transmission power level. To alleviate transmission conflicts, the backoff method with transmission power adaptive mechanism has been proposed. Based on the large-scale simulations, we validate that our design can reduce flooding delay with small extra energy expenditure compared with conventional flooding schemes.

Energy harvesting capability makes it possible to maintain network sustainability for wireless sensor networks. Due to the dynamics and instability of energy, it is significant to efficiently utilize the harvested part to keep the network sustainability. In this work, a Sustainable Clustering Protocol (SCP) is devised to provide continuous and timely data collection for sensor networks with ambient energy harvesting, such as solar power. In SCP, cluster heads (CHs) are only responsible for cluster coordination within clusters. In addition, cluster relays (CRs) are selected to share the data aggregation and long-haul forwarding responsibilities of original CHs. Consequently, network infrastructure is stably maintained since only intra-cluster CRs instead of CHs are selected periodically, which in turn decreases control overhead. Simulation results show that sustainable clustering can efficiently balance the energy consumption of all nodes and improve the sustainability of network compared to traditional clustering protocols.

Battery-powered sensor networks are often duty-cycled to conserve nodes energy and prolong network lifetime. In such intermittently-connected networks, the waiting time over multi hop data forwarding dominates delivery latency, which is the main challenge and unacceptable for delay-sensitive applications. In this work, we address the optimisation problem for duty-cycled sensor network with transmission power control. In particular, we propose dynamic transmission power switch (DTPS), a cross-layer approach which jointly considers power control with multi parent forwarding for the fast data collection. In DTPS, each node dynamically selects a sequence of transmission pairs to deliver data packets. Extensive simulation results show that our scheme can reduce both delivery delay and energy consumption for data collection applications.

Energy harvesting and recharging techniques have been regarded as a promising solution to ensure sustained operations of wireless sensor networks for long-term applications. To deal with the diversity of energy harvesting and constrained energy storage capability, sensor nodes in such applications usually work in a duty-cycled mode. Consequently, the sleep latency brought by duty-cycled operation is becoming the main challenge. In this work, we study the energy synchronization control problem for such sustainable sensor networks. Intuitively, energy-rich nodes can increase their transmission power in order to improve network performance, while energy-poor nodes can lower transmission power to conserve its precious energy resource. In particular, we propose an energy synchronized transmission control scheme (ESTC) by which each node adaptively selects suitable power levels and data forwarders according to its available energy and traffic load. Based on the large-scale simulations, we validate that our design can improve system performance under different network settings comparing with common uniform transmission power control strategy. Specially, ESTC can enable the perpetual operations of nodes without sacrificing the network lifetime.

Data query is a common communication pattern in sensor networks.However, due to the introduction of sleep latency, it is challenging to perform efficient query in low-dutycycle sensor networks.In particular, the round-trip delay from the sink to source nodes and vice versa over the same forwarding path could be extremely long.In this work, westudy the delay optimization problem by jointly considering routing and sleep scheduling, then propose a holistic scheme to find the asymmetric routing paths for data query and response so that the round-trip delay could be minimized.We compared ourMinimum Delay Query (MDQ) deign with the state-of-the-art schemes.The evaluation results verify that our design can greatly reduce the query delay in low-duty-cycle sensor networks.

Low-duty-cycle operation has been adopted to alleviate the consumption rate of energy, which is significant for the power scarcity sensor networks. The sleep latency brought by low-duty-cycle mode, however, leads to a dramatic increase of delay, which may not be tolerable for delay-sensitive applications. In this work, we introduce the transmission power control mechanism into low-duty-cycle sensor networks. Particularly, we propose Delay-bounded Transmission Power Control (DTPC), a cross-layer approach, to minimize the energy consumption of sensor nodes while meeting the user-specified delay constraint. In DTPC, each node builds its own transmission table using dynamical programming and then adaptively selects the approximate forwarding entry according to the delay bound. In addition, our design is embedded to support both single-parent and multi-parent data forwarding scheme. The extensive simulations and test-bed experiment results show that DTPC can guarantee the delay bound with much lower energy cost compared with other well-known schemes.

Duty-cycled operation has been introduced as an efficient way to preserve nodes energy and prolong network lifetime for wireless sensor networks. However, such networks are often logically disconnected since there is a limited number of active nodes within a period of time. Traditional routing algorithms, which have been designed for always-awake wireless networks, suffer excessive waiting time incurred by asynchronous schedule of nodes and cannot be applied to these time-dependent sensor networks. In this work, we study the optimization of delivery delay for low-duty-cycle sensor networks. Specially, we theoretically analyze the sleep latency in low-duty-cycle networks and present a new routing metric, which takes both lossy link and asynchronous schedule of nodes into consideration. Based on the metric, we propose delay-driven routing algorithms to find optimal forwarder in order to reduce delivery delay for source-to-sink communication. We compare our design against state-of-the-art routing algorithms derived in wireless networks through large-scale simulations and testbed experiments, which show that our algorithms can achieve a significant reduction in delivery delay.

Geographic forwarding has been widely studied as a routing strategy for mobile ad hoc networks, mainly due to the low complexity, scalability of the routing algorithm. However, in a network with routing holes, existing geographic routing schemes such as GPSR, GOAFR could cause the throughput capacity to drop significantly due to concentration of traffic on the face of the holes. The slope-based stateless routing algorithm SBRA for mobile ad hoc networks with holes is proposed firstly in the paper, which does not need to maintain global network topology and can solve the local minimum problem and enhance the network throughput. In order to improve the performance of routing algorithm further, we propose a routing path discovery algorithm SBRDA, which can discover two routing paths to detour a hole, then it selects a shorter one. We also propose a slope based landmark discovery algorithm SBLDA, the greedy routing is combined with our landmark discovery scheme to build routes, which can solve triangle problem and achieve good routing performance. The performance of the proposed algorithms is evaluated by means of simulation.

One fundamental task of wireless sensor networks (WSNs) is to collect useful information from the sensory field or response users query. In such scenario, the gigantic amount of individual sensor readings will converge to the base station (BS) of the network. Thus, the “funnelling effect” which describes the convergence of data traffic towards data sinks remains a major threat to the network lifetime. In particular, those sensors near data sinks need to relay data for nodes that farther away and burn energy faster with the result that the network may become disconnected or dysfunctional. In this paper, we investigate a heterogeneous sensor network by introducing a few mobile elements1, referred as aggregators into static sensor network and utilize the mobility to alleviate the ”funnelling effect”. In particular, these aggregators deploy themselves and worked as cluster heads. In such mobility-assisted hierarchy, we study the aggregator deployment problem for energy conservation and consider the integration of mobility and routing algorithms for lifetime elongation. Based on the extensive simulation, we show that such mobility-based hierarchy can significantly mitigate the ”funnelling effect” and then prolong network lifetime.

High energy-efficiency and low transmission delay are most important for periodical data gathering applications in wireless sensor networks (WSNs). Therefore, the product of energy consumption and transmission delay, EnergyxDelay is a good metric for such performance evaluation. This paper presents a distributed energy-efficient and delay-aware data gathering protocol, which is efficient in the ways that it prolongs the lifetime of network, as well as takes less time to finish a transmission round. The simulation results show that it improves the average EnergyxDelay metric compared to other protocols.

One of the main challenges for a sensor network is conserving the available energy at each sensor node and then prolonging the network lifetime. Many energy efficient/conserving routing protocols have been proposed to the issue; however, the “funnelling effect” in multi-hop communications which describes the convergence of data traffic towards the static sinks (Base Stations) remains a major threat to the network lifetime. This is because the sensor nodes located near a base station have to relay data for those nodes that are farther away. In this paper, we introduce a few mobile elements, named aggregators into network and study their mobility strategies. In particular, we propose a Local Aggregator Deployment Protocol for Energy Conservation (LADPEC) and consider the integration of mobility and routing algorithms for lifetime elongation. Based on the simulation results, we show that joint mobility and routing would significantly increase the lifetime of network.

Security bootstrap is important to the platform security. If the bootstrap is not secure, Rootkits, Viruses and Trojan horses may be loaded into kernel, thus the following defenses built on the compromised kernel may be useless. In this paper, a trusted-computing based security bootstrap is introduced. We modify trust chain defined by Trusted Computing Group slightly by introducing a new component called PMBR, to implement a more flexible security bootstrap. Comparing against existing works, our contributions are as follows: (1) Our approach can automatically recover programs being attacked. Furthermore, the "attack codes" inserted by attackers can be extracted and their corresponding physical addresses can be located at the same time. (2) We theoretically prove the security of the modified trust chain. (3) We investigate the formal development of PMBR based on B method.

With the introduction of resource-rich mobile elements into wireless sensor networks, the energy-efficiency of such network can be enhanced. In this paper, we study the deployment problem of these mobile elements. A novel potential-field-based coordination protocol, named Aggregator Deployment Protocol for Energy Conservation (ADPEC) for wireless sensor networks is proposed. The proposed protocol is aimed to move the mobile aggregators to the desired locations in a distributed and cooperative way, where the energy dissipation of individual sensor will be balanced and the energy efficiency of the network will be maximized. Our experiment results show that ADPEC improves the energy efficiency and prolongs the lifetime of network compared to static or random deployment protocols.

Cluster-based routing protocol has been demonstrated as a good way to meet the requirements of wireless sensor networks (WSNs), such as scalability, lifetime constraint and energy-efficiency in LEACH. On one hand, the creation of clusters can lower energy consumption within a cluster by performing data fusion to decrease the amount of sensed data forwarded to BS (base station). On the other hand, the formation of cluster can consume lots of energy and then increase additional overhead. Therefore cluster formation algorithm which decides how to select cluster and how to schedule nodes is crux in cluster-based related routing protocols. In the paper, we propose a distributed weight-based clustering algorithm for WSNs which takes battery usage, load balancing and MAC functionality into consideration. Simulation results demonstrate the energy-efficiency of the proposed algorithm

WSNs (wireless sensor networks) are often high-densely deployed and nodes are easy to fail. All these uncertainty preclude manual configuration and design-time pre-configuration. In the paper, MTLT (mixed type logical topology) is proposed, by which the whole sensor network is organized as mixed-type logical topology according to the local density and energy constraint. Simulation experiments proved that MTLT is a simple, robust and low-latency topology for different types of data dissemination in dense deployed WSNs.