The learning content selection process is triggered at every user request for learning content. During this process a list of suitable LOs is generated by an oPL system. The PL system first selects those LOs that match learning objectives relevant to the learning outcome (relevant LOs). Next a subset of these latter LOs that best match learner characteristics is chosen as the basis for a presentation suitable for the learner before it is finally delivered it to the learner’s device. When the oPOAA solution is deployed in conjunction with the oPL system, the content selection process is enhanced to select the best connected remote hosts in order to minimise the content download latency. The LO selection process is illustrated in Figure 4-3.
Relevant Learning Objects Learning Objects Relevance Selection Suitable Learning Objects Learning Objective Personalisation User Profile oPOAA Performance Rating Selected Learning Objects
Figure 4-3: Performance-aware Learning Objects Selection Process
The first step is relevance selection where the PL system identifies the learning objective and selects LOs matching the learning outcome. The second step is personalised selection where the oPL system shortlists a number of the most suitable LOs based on the user’s learning profile. The oPL system also assigns a LO suitability rating for the requesting learner. LOs may be distributed across several remote DER servers. oPOAA-enhanced selection introduces the third step – network performance-aware assignment where the oPOAA agent estimates a performance rating for each hosting server (for each suitable LO). This performance rating is based on the performance history of the DER hosting the selected LOs.
4.2.2 Architecture and Components
oPOAA continuously monitors network conditions between the oPL system and DER servers to determine network performance without employing an agent at the DER side. Network parameters considered relate to content delivery performance and include download time and delay. They are inferred from historic performance information gathered across a number of recent sessions with the DERs in question. The block-level architecture for the oPL system incorporating oPOAA is shown in Figure 4-4. In addition to the typical components of an oPL system, such as the Adaptation Engine, User Model, Domain Model, Figure 4-4 shows the three new oPOAA components, namely the oPOAA Performance Model (oPOAA PM), oPOAA
Domain Model (oPOAA DM) and oPOAA Performance Engine (oPOAA PE).
Campus Gateway Campus
Network open PL system User Model Learner Viewing Device M Domain Model Adaptation Engine Content Model Performance Model Learner Viewing Device 1 Adaptation Engine oPOAA Remote Server N Remote Server1
Figure 4-4: oPOAA Block-level Architecture
oPOAA Performance Model (oPOAA PM) is a passive component of the oPOAA. It stores
information used by the oPOAA Performance Engine. Each DER is assigned a unique identifier. The oPOAA PM maintains a history log for each connected DER (DER log). The log is a sliding-window structure that contains network performance-related readings for the most
recently requested content from a given DER. The following readings are maintained for a number (X) of the most recently delivered LOs from each DER:
LO_ID: LO identifier, unique within the oPL system Domain Model;
Delivered: delivered content that reached the learner device (measured in Kb);
RTT (Round Trip Time): the time required to send a message over a link to this DER and receive a response (measured in milliseconds);
Duration: the time interval between the content request and the completion of the content delivery (measured in milliseconds);
Time Stamp: the date and time of the LO request.
Sample content from a DER log is given in Table 4-3. The throughput is calculated as Delivered over Duration and it is measured in Kbps.
LO_ID Delivered RTT Duration Time Stamp Mat980 4480 45 2500 2014-10-30 08:30
Mat344 59 35 300 2014-10-30 10:45
Table 4-3: DER Log - Sample Content
oPOAA Content Model (oPOAA CM) is the other oPOAA passive component. It acts as a link
between the oPL system Domain Model and oPOAA PE (as shown in Figure 4-4) and provides information about the LOs from the Suitable and Relevant LOs (SRLO) list (described in Section 4.2.3). LO details, such as ID, size and locations (URLs) are required to perform performance aware selection. Sample LO information is provided in Table 4-4.
LO_ID LO_SIZE LO_ID DER_ID URL
Mat980 4500 Mat980 DITDER1 http://www.dit.ie/~lejlar/video/Diff.mpg Mat344 60 Mat980 DCUDER3 http://www.dcu.ie/~lejlar/video/Diff. mpg
Table 4-4: LO Details (a) and Locations (b)
oPOAA Performance Engine (oPOAA PE) is the active component of oPOAA that calculates
performance ratings for all suitable and relevant LOs suggested by the oPOAA CM at each learner request. Furthermore, oPOAA PE selects DERs to be contacted and schedules requests for each LO in the SRLO list.
Performance ratings are based on network conditions, therefore the oPOAA PE requires data on the state of the links to the DERs. The quantity of additional traffic introduced by a monitoring solution should be minimised to avoid consuming valuable network bandwidth resources. The proposed solution collects as much information as possible without employing software agents on the DER and learner sides. oPOAA was proposed to cater for end users (learners) who are typically reluctant to install third-party software on their devices. User behaviour has significantly changed with the increased popularity of smartphone applications. However, DER owners and administrators remain reluctant to install and run third party software. Therefore
oPOAA PE collects data (request time, requested size, delivery time) for each LO requested and delivered, and calculates DER performance information that is then recorded by the oPOAA PM to DER logs.